In today’s global business environment, companies increasingly partner across borders, forming diverse teams that bring together different nationalities and cultural perspectives. While these collaborations offer significant opportunities for innovation, they also present challenges, particularly when it comes to managing change. Ensuring the success of change initiatives in culturally diverse teams requires businesses to address the unique hurdles posed by cultural differences, communication styles, and geographically dispersed teams.
From our consulting experience, we’ve seen that managing these challenges demands structured approaches that address cultural and communication barriers. It’s not about prescribing a one-size-fits-all solution but finding the right tools to adapt to the specific cultural contexts of the teams involved.
Common Challenges in Global Teams
Global organizations often face recurring challenges when working with culturally diverse teams. Some of them are:
Managing Cultural Differences in Practice
Here are some practical tools and strategies that we’ve found effective in managing cultural diversity:
- Cultural Awareness Workshops
Cultural awareness is more than a formality—it’s an essential starting point for collaboration. We’ve found that offering targeted cultural awareness training helps team members understand diverse perspectives and workplace behaviours. For example, in hierarchical cultures, employees may defer to authority, while in more egalitarian cultures, decision-making tends to be participatory. By educating employees on these differences, workshops enable better communication across hierarchical and cultural divides. - Social Engagement and Team-Building Activities
Building trust and rapport is crucial for change initiatives to succeed, particularly in collectivist cultures where group harmony is prioritized. Organizing social activities or team-building exercises helps break down barriers and fosters a culture of openness. These activities also contribute to work-life balance in more indulgent cultures, improving team satisfaction and cohesion. - Establishing Ground Rules and A Common Vision
Establishing clear ground rules—such as prioritizing the company’s success, encouraging accountability, and fostering collaboration—ensures that all stakeholders are aligned and working towards the same goal. This helps streamline interactions and creates a structured framework for effective teamwork across cultural boundaries. - Stakeholder Mapping and Engagement Plans
Identifying key stakeholders and understanding their influence is vital in high power distance cultures, where leadership approval may hold significant weight. In cultures with high uncertainty avoidance, early and frequent stakeholder engagement reduces resistance to change. Effective engagement plans ensure that stakeholders are kept informed and that their feedback is integrated throughout the change process. - Unified Communication Platforms and Escalation Processes
Clear communication is a cornerstone of managing change. A unified communication platform allows teams to share updates, raise concerns, and provide feedback, no matter their location. In high uncertainty avoidance cultures, defined escalation processes offer security and clarity, while in more individualist cultures, such platforms empower team members to voice concerns directly. - Empowering Local Leadership and Change Agents
Local leadership plays a key role in bridging cultural gaps. Leaders’ familiar with local customs can adapt change initiatives to meet their team’s expectations. In hierarchical cultures, empowering local leadership ensures that change efforts respect the existing structure, while in collectivist cultures, local leaders can foster group consensus and collaboration, making change more sustainable. - Feedback Loops and Continuous Improvement Mechanisms
Regular feedback loops are essential to address concerns early and adjust change initiatives based on real-time input. We’ve found that continuous improvement mechanisms are especially effective in long-term-oriented cultures, where gradual growth is highly valued. In high uncertainty avoidance cultures, frequent feedback reduces fear and builds confidence in the change process.
Case Study: Managing Collaboration Across Multiple Stakeholders in a Global Transformation
In one of our recent engagements, we worked with a client facing the challenge of managing collaboration across multiple stakeholders—both internal and external—spanning several regions, including the UK, Sweden, the US, and India. The complexity of this setup was compounded by the fact that different cultures, priorities, and working styles needed to be aligned for the transformation to succeed.
To address these challenges, the company implemented several ground rules that ensured effective collaboration:
- Put the Company First: This principle guided all stakeholders to prioritize resolving business problems over individual disagreements. It helped to maintain focus on the company’s overall success.
- Be Accountable: Everyone was expected to demonstrate accountability for their roles and responsibilities. This fostered a sense of mutual responsibility, encouraging transparency and ownership.
- Work Collaboratively: The mantra was simple but powerful—everyone’s efforts collectively contributed to the company’s success. This reinforced the importance of partnership across internal teams and external suppliers.
- Share Knowledge: Knowledge sharing was emphasized as essential to the success of the transformation. All stakeholders, whether internal or external, were encouraged to ensure that no part of the ecosystem was left unprepared.
Alongside these ground rules, we facilitated cultural awareness training to help the teams understand the diversity in communication styles, decision-making processes, and approaches to authority across different regions. This holistic approach—combining structured ground rules and cultural sensitivity—ensured that all stakeholders, regardless of location, could work together cohesively and achieve the desired outcomes.
Conclusion: Communication, Relationships, and Psychological Safety as Catalysts for Success
Managing cultural differences in global teams requires more than just awareness—it demands flexibility, trust, and a commitment to continuous learning. From our experience, the most successful teams are those that understand the pivotal role of communication and relationships in bridging cultural divides. Open, flexible communication fosters trust and builds psychological safety, where team members feel comfortable expressing their ideas and concerns without fear of judgment. This environment of psychological safety is crucial in diverse teams, as it encourages open dialogue and supports collaborative problem-solving.
Equally important are the relationships within the team. Strong personal connections, built through both formal and informal interactions, help break down barriers and create a sense of unity. These relationships make it easier for team members to navigate cultural differences and collaborate effectively, even in high-pressure situations.
By embedding communication, psychological safety, and relationship-building into the core of your change initiatives, organizations can turn cultural diversity into a strength. When teams embrace cultural differences as an asset, not a challenge, they unlock the full potential of their global workforce. This inclusive, adaptive approach not only enhances collaboration but ensures the long-term success of your initiatives.
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As digital business transformation becomes increasingly vital, management is willing to embark on initiatives that are expensive and both time and resource-intensive. But are these initiatives successful? How can progress and results be assessed? Many organizations invest heavily in digital technologies but are unable to determine if the investment has generated value or if they are headed in the right direction.
Digital transformation can go beyond technology and envelop the entire business. Successful digital initiatives require a strategic approach, strong leadership, employee engagement, and a focus on meeting customer needs. According to Harvard Business Review, although 89% of large companies globally have a digital and AI transformation underway, only 31% have captured the expected revenue lift and 25% have seen expected cost savings from the effort.
As digital projects become more complex and resource-intensive, it becomes necessary for organizations to quantify their impact effectively. A clear framework can help align initiatives with strategic goals, optimize resource allocation, manage risks, and make informed decisions. This in turn can foster a culture of continuous improvement and innovation. It can further ensure that digital projects not only deliver immediate benefits but also contribute to long-term organizational growth. This enables the management team to prioritize scalable initiatives capable of substantially improving the organization’s performance with fast, minimally viable outcomes that can be improved over time.
A measurement framework is key to digital transformation success
Unfortunately, this is an oversight that undermines many transformations before they even begin. It becomes easier to course-correct with a framework to identify weak points and monitor progress. A digital initiative is different for every organization and there are no universal metrics that can make it easy.
Figure 1: Building a framework for measuring impact of digital transformation projects
So, where do we start to identify the right metrics and KPIs? Organizations must focus on what they want to achieve with the transformation efforts and assess their digital maturity level to identify the right set of KPIs. Once the KPIs are identified, one must have the tracking and monitoring systems in place along with a robust reporting mechanism to enable analysis and decision making.
Focus on the right metrics to guide your initiative to success
Before introducing any KPIs, it would make sense to set the context by answering some preliminary questions. For instance, what are the key drivers for the digital project? Do we have the right systems to collect and analyse data necessary for the said KPIs? Organizations should understand their digital maturity levels and drivers for the project before establishing the right set of KPIs.
Figure 2: Measuring Digital Business Transformation
Organizations can have different objectives for their transformation initiatives, and they should begin by aligning KPIs with organizational goals, ensuring they reflect desired business outcomes. They can start by involving key stakeholders to identify relevant metrics that impact various departments. Every stakeholder may look at different metrics depending on their roles, and it is thus important to keep them informed, take feedback and incrementally course correct if necessary.
As the business objectives evolve, regular review and adjustment of KPIs can enable continuous improvement and successful digital transformation. When discussing the importance of measuring the success of any transformation project, we can draw on our experiences from previous projects at Opticos.
Every organization tracking its digital transformation progress will naturally employ various measurement tools. Given that the selection of these tools impacts the efficiency of measurement efforts, as well as the workloads and workflows of their users, selecting the right tools can significantly enhance the overall effectiveness of the transformation program.
Opticos provides expert knowledge and helps organizations to develop successful frameworks, analyse current reporting mechanisms, establish robust KPIs and identify the right tools for measurement. Contact us to know more.
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Introduction
The global business landscape is evolving rapidly, marked by technological disruptions, geopolitical tensions, and a heightened focus on sustainability. As an independent Management Consulting firm supporting clients with their business transformation initiatives, we at Opticos felt the need to understand how companies, especially global corporates with roots in the Nordics, are navigating through turbulent change.
So, we decided to interview senior executives from four leading companies in their respective industry verticals: Essity, Trioworld, Securitas, and SAS. In these candid conversations, senior leaders shed light on their strategic vision, discuss the impact of Artificial Intelligence (AI) and automation, their approaches to mitigating risks amid economic and geopolitical uncertainties and various other business aspects.
Expert panel:
- Andrew Lord, Group CFO at TrioWorld
- Martin Althén, President at Securitas Digital
- Carina Malmgren Heander, Senior Advisor at SAS
- Ulrika Kolsrud, President, Health & Medical at Essity
The highlights of these discussions, including their insightful perspectives and forward-thinking ideas, are summarised here in this article.
1. Assessment of Overall Business Climate in Sweden
The executives acknowledge the challenging business climate globally and in Sweden over the past few years, citing factors like the COVID-19 pandemic, inflation, supply chain disruptions, and changes in consumer behaviour stemming out of these factors. However, the leaders note that signs of economic recovery are showing and highlight their companies’ agility and resilience in navigating these turbulent times.
Ulrika Kolsrud: “Regulatory changes, especially the Medical Device Regulation (MDR) in Europe, have burdened the health sector with significant adaptation costs. Inflationary pressures and rising costs have been especially challenging to manage in the regulated health care sector, characterised by long-term contracts and public funding. Despite these hurdles, Essity is in a better shape than ever, although it contends with customers opting for cheaper, lower-quality alternatives.”
Andrew Lord: “Trioworld is in a great position at the market now, even as it emerges from a dynamic and uncertain business climate, with shocks such as COVID, changes in demand and consumer behaviour, and increased competition from cheap imports. Trioworld has successfully adapted to these challenges by being agile, restructuring, improving margins, and expanding in recycling and North America.”
Martin Althén: “There has been a significant slowdown amidst high inflationary pressure over the past few years, with companies launching cost reduction programmes. However, even as interest rates start to reduce, we are now slowly leaving the high inflationary period into a more stable economy.”
Carina Malmgren Heander:
2. Views on Growing Geopolitical Uncertainties and Mitigation Strategies
Organizations around the globe have been facing turbulent situations due to ongoing geopolitical tensions. The executives expressed their concerns regarding this and acknowledged the adverse impact on supply chains, operations, and related risks. At the same time, it presents a timely opportunity to implement strategies to monitor, mitigate, and address these uncertainties.
Ulrika Kolsrud: The growing geopolitical uncertainties and their impact on the business are a critical concern. Additionally, the Russia-Ukraine conflict disrupted supply chains, necessitating a reassessment of the supply chain in line with geographical expansion goals. To address the risks associated with geopolitical uncertainties, the company engages in scenario planning. This involves analysing macro trends and considering them in strategic and tactical decision-making processes.
Andrew Lord:
Martin Althén: “The geopolitical trends involving the rise of nationalist mindset, protectionism and artificial barriers to entry are hard realities that may likely get worse in the near future. In our business, we have actually stopped operations in 11 countries the past 2-3 years where we concluded we could not conduct good business aligned with our values, code of conduct and ethics.”
Carina Malmgren Heander: “Geopolitical tensions primarily affect us through closed borders and overflight permissions. For instance, we currently can’t fly over Russian airspace. However, we haven’t seen a significant increase in fear of travel due to these uncertainties. It’s more about practical considerations. We continuously monitor the situation and make adjustments.”
3. Implications of AI and AI Roadmaps
AI is viewed as a strategic priority for all companies, with roadmaps and initiatives in place to leverage AI for enhancing operations, efficiency, and customer experiences. While traditional AI is being applied primarily for optimization, generative AI presents new, unchartered opportunities. However, risks around AI governance, ethics, and cybersecurity remain primary concerns.
Ulrika Kolsrud: “AI is a high priority for Essity. The company has mapped out where it sees the greatest benefits of AI, whether internal or external, in daily operations or transformative game-changers. Essity views AI more as an opportunity than a threat.”
Andrew Lord: Andrew takes a slightly cautious approach to embracing AI for their business in the short term. “We are not yet fully leveraging AI to improve our business processes but are evaluating various potential solutions”. For example, we have embedded Microsoft Copilot into our business process primarily because of the maturity of the solution.
Martin Althén: “We use traditional AI quite extensively, alongside deploying generative AI models. We have a very clear AI strategy and roadmap for what to do, how to do it, and how to implement and scale AI workflows through federated teams and ambassador roles across the organization to accelerate our business transformation with AI’s help.”
Carina Malmgren Heander: “AI is primarily being used to enhance customer experiences, personalization, and internal efficiencies. At SAS, we’re using AI in areas like customer service, communication, and developing customized offers for our loyalty program members based on their preferences and travel history.”
4. Companies’ Sustainability Efforts and Alignment
Sustainability is a core priority that is deeply ingrained in decision-making processes of these companies. Efforts include environmental goals such as emissions reduction and waste management, social responsibility through ethical employment practices, and robust governance. Executives highlight sustainability as a competitive differentiator.
Ulrika Kolsrud:
Andrew Lord: “Trioworld has a strong position in the market for circular solutions, as the EU legislation and the ESG agenda of the investors are driving the demand for recycled and low-carbon plastics. Trioworld has invested in innovation and technology to produce high-quality products from recycled materials and reduce its environmental impact.”
Martin Althén: “Sustainability has long been part of Securitas’ core values with demanding standards. More recently, we have expanded into areas like actively promoting diversity and inclusion as our industry has been historically male-dominated. Securitas was the first worldwide security company to sign the Science Based Targets initiative commitments.”
Carina Malmgren Heander: “Sustainability has been a priority for SAS for over 15 years. We’ve focused on optimizing flight routes, investing in more fuel-efficient aircraft, and participating in programs for developing electric and hydrogen-powered aircraft. We’re working with governments to incentivize sustainable aviation fuel (SAF) production and make it more accessible.”
CXO Perspectives
Talent Strategies in the Post-Pandemic Era
Global talent dynamics has taken a shift after the pandemic and when asked about the same Carina said, “During the pandemic, we had to furlough up to 90% of our workforce and lay off 5,000 employees. As demand rebounded, we faced challenges attracting and retaining talent, as many had left the industry. We’ve worked on enhancing our employee value proposition, offering remote and flexible working arrangements, and expanding our talent pool globally for specialized roles.”
Adding to this, Carina also spoke on how they are taking advantage of the AI boom to their advantage at SAS. “Leveraging AI to better match employee skills with assignments and create an internal talent marketplace” is listed as a key opportunity and challenge.
Securitas Tech Outlook: Opportunities in Digital, AI, Robotics
Securitas identifies several significant opportunities and risks that will shape their strategy in the coming years. Speaking about the top technological opportunities Martin said, “There are three key technology areas I see intersecting for us over the next 5 years – digital, AI and robotics. We are capturing more and more information delivery digitally. We will automate insights and response actions from that digital data through AI analytics. And we will increasingly deploy the appropriate robotic response option.”
One notable application is the use of AI as a verbal chat interface for security officers’ shift reporting. Guards can now report verbally in their natural language, increasing report frequency and detail. The AI then refines these reports, adjusting length, removing inappropriate content and sensitive information, and ensuring GDPR compliance. This system improves both the quantity and quality of reports, demonstrating the company’s commitment to leveraging AI’s potential across its operations.
The CFO’s Roadmap for Inspired Leadership
Andrew talks about the leadership traits that are important for the businesses, and believes Trioworld excels at fine-tuning successful operations but acknowledges that addressing more challenging issues requires a different approach.
Adding to this he said, “Drawing from my own experience, I can assert that achieving turnarounds involves a hands-on approach. You need to identify and address problems swiftly. I value starting each year by clearly outlining goals and targets on a whiteboard to effectively communicate my vision to my finance team. This ensures everyone is aligned, inspired, and forward-thinking about the company’s direction and adaptability.”
Healthcare Industry: Navigating Turbulent Waters
When we asked about the state of the healthcare industry, “It’s been a rough ride”, Ulrika told us. She went on to explain that it wasn’t just COVID-19 causing headaches. ‘You know, we’ve had these new regulations come in – the Medical Device Regulation in Europe. It’s been a real challenge to keep up our ambitious innovation agenda, when we’ve had to invest a lot of time and money to secure compliance.’
‘Then there’s inflation. Costs are going up, and when you’re dealing with long-term contracts like we are, that really squeezes you.’ Despite all this, Essity has emerged from this testing period stronger, with a sense of greater internal stability and looking to improve its position in the market for the longer run.
The Final Word
While many interesting aspects about business and leadership were highlighted and discussed, three things clearly stood out for us:
- Innovation is one of the key levers to navigate through change: They may not necessarily be disruptive or path-breaking solutions but incremental changes that can create a positive impact on the business.
- You may love or hate AI but can never ignore the transformative impact it will have on your business. If handled responsibly, an effective AI roadmap will deliver a sustainable competitive advantage for your business.
- Sustainability should transcend metrics and reporting to be a way of life. Business leaders should lead by example and take bold decisions to lead their companies into a sustainable future for the next generations.
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Introduction
Change management is a crucial process for any organization preparing to transition from one state to another. At Opticos, we understand that driving change means not just implementing new strategies but anchoring them within the organization to achieve long-lasting effects. Our experience in change management has shown us that the key to success lies in addressing four fundamental areas: Motivate, Involve, Enable, and Empower. These areas are applicable irrespective of the change management framework chosen, ensuring their universal relevance and effectiveness.
Motivate: Creating the Drive for Change
The first stage of any change management process is motivation. At Opticos, we believe in preparing minds through clear communication of the benefits and necessity of the change. This is done through:
- Establishing a Clear Vision: We develop a concise, inspiring vision of the future state that resonates with all stakeholders.
- Aligning Objectives: By aligning the change with the organization’s strategic goals, we ensure everyone understands its importance.
- Creating Enthusiasm: Through inspirational leadership and communication, we generate excitement and commitment towards the change.
Involve: Engaging Stakeholders
Successful change cannot happen in isolation. Involving stakeholders at every level is crucial. We do this through:
- Psychological Safety: We create a safe environment where team members feel comfortable sharing their perspectives and concerns.
- Inclusive Decision Making: By involving diverse viewpoints, we ensure decisions are well-rounded and widely accepted.
- Active Participation: Encouraging active participation from all stakeholders helps build ownership and accountability for the change.
Enable: Facilitating the Change Process
Enabling involves creating an environment that supports the change and makes it sustainable. Our approach includes:
- Training and Development Programs: Comprehensive training programs equip employees with the skills needed for new ways of working.
- Support Systems: Building robust support systems, including mentoring and coaching, guides employees through the change.
- Delegating Authority: Empowering teams with the authority to make decisions gives them a sense of ownership and helps accelerate the change process.
Empower: Equipping for Success
Empowerment involves providing the necessary tools, authority, and confidence to embrace change. We achieve this by:
- Infrastructure and Resources: Providing the necessary infrastructure and resources to support new processes and technologies.
- Continuous Improvement: Implementing feedback loops to continuously refine and improve the change process.
- Reinforcement: Reinforcing new behaviours through recognition and rewards ensures that the change is anchored and becomes part of the organizational culture.
Opticos’ Proven Framework
At Opticos, our change management framework is agnostic, allowing us to tailor our approach to the specific needs of each organization. We leverage well-known frameworks such as Kotter’s 8-Step Process and Prosci’s ADKAR model, integrating them into our unique toolbox to drive successful outcomes.
Conclusion
Change is not a straight line, and navigating it requires careful planning and execution. At Opticos, our expertise in motivating, involving, enabling, and empowering teams has helped numerous organizations achieve their desired business benefits through effective change management. Our commitment to sustaining change ensures that it goes beyond implementation and has a lasting impact on the organization.
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Introduction
Manufacturing companies face increasing pressure to optimize operations, reduce costs, and enhance competitiveness. To meet these challenges, manufacturing and supply chain companies are turning to predictive manufacturing. This approach leverages advanced analytics and AI algorithms to anticipate disruptions, optimize production processes, and enhance overall efficiency.
Moving effectively towards predictive manufacturing requires a strategic approach and the right tech solutions. In this article, we’ll explore the role of AI in predictive manufacturing, its key use cases, best practices, and steps for businesses to get started.
Industry 4.0 and predictive manufacturing
Industry 4.0 is the ongoing automation of traditional manufacturing and industrial practices using smart tech. It is a fusion of technologies that blur the lines between the physical and digital domains. Six primary technologies are driving Industry 4.0; internet of things, cloud computing, artificial intelligence, federated AI, cybersecurity and digital twins.
Convergence of technologies enabling predictive manufacturing
The convergence of these technologies creates a more intelligent and connected manufacturing environment, offering real-time analytics, increased flexibility and efficiency and customer-centric manufacturing.
Enabled by these tech developments, predictive manufacturing is a data-driven approach that uses historical and real-time data to forecast future events and outcomes in the manufacturing process. It involves leveraging advanced analytics techniques, such as machine learning and predictive modeling, to analyze data from various sources, including sensors, equipment, and production systems. By identifying patterns, trends, and anomalies in the data, predictive manufacturing enables companies to make informed decisions, optimize processes, and mitigate risks.
When manufacturing machinery are fully integrated with digital systems, real-time data collection and analysis becomes possible, and this data can then be used to optimize production processes, predict maintenance needs, and improve overall quality control. Automation enables process efficiency and predictive algorithms enable supply chain flexibility, ultimately where the entire supply chain becomes more agile to support customer-centric manufacturing.
Building a resilient, sustainable and efficient supply chains through digital twins
There are many applications and use-cases to be explored with these technologies, but the ability to build resilient, sustainable and efficient supply chains is perhaps one of the most interesting. Imagine a supply chain fully modeled as a ‘digital twin’, including the manufacturing process, where the physical equipment is fully integrated with digital systems, offering a real-time view of your supply chain flows. While this is a daunting task, value can be realized in a stepwise manner. For example, benefits can already be created with an isolated view of 1) the manufacturing process, or 2) with a limited extension down- or up-stream.
Digital twins leverage the data and connectivity of Industry 4.0 to create a dynamic digital counterpart that reflects the real world. This allows for better decision making, improved efficiency, and overall optimization across the entire manufacturing process. A digital twin is essentially a virtual representation of a physical object, process, or system. It’s constantly updated with data from the physical counterpart using IoT sensors. This creates a bridge between the physical world and the digital world, allowing for better monitoring and analysis. This can also be extended with concepts like federated AI/machine learning to further enhance dynamic adaptability, privacy and data security. In essence, the combination of federated AI and digital twins creates a dynamic and collaborative manufacturing ecosystem. Factories can leverage the power of AI and real-time data, while still maintaining data privacy, to optimize processes, improve efficiency, and drive innovation across the industry.
Creating value from digital twins
There are four pockets of distinct value to be explored: efficiency gains, innovation, supply chain resilience and sustainability. This value can be illustrated through a set of straight-forward use-cases; how to sharpen foresight, optimize production, securing delivery and reduce environmental impact.
Sharpening foresight: AI for predictive maintenance
The factory utilizes digital twins for equipment health monitoring. Historical maintenance data is analyzed to identify common failure patterns and lead times for specific equipment types. This allows for:
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Developing predictive maintenance schedules based on equipment usage and sensor data from the digital twin.
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Proactive stocking of spare parts most likely to fail, minimizing downtime.
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Optimizing technician training by focusing on the most common maintenance tasks identified through historical data analysis.
Optimizing production: AI for efficiency
The factory leverages digital twins to track production processes in real-time. Data analysis from the digital twin identifies bottlenecks and inefficiencies. This allows for:
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Simulating production scenarios using the digital twin to test potential solutions for bottlenecks.
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Investing in targeted automation solutions to address specific bottlenecks identified by the digital twin.
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Optimizing production line layouts based on data insights to improve material flow and reduce processing times.
Securing delivery: AI for supply chain resilience
The digital twin tracks inventory levels and production capacity. Advanced data analytics are implemented on historical supplier and logistics data to predict potential disruptions. This allows for:
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Identifying alternative suppliers and negotiating backup agreements with the orchestrating party to ensure parts availability.
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Maintaining buffer stock of critical materials based on historical usage patterns and lead times.
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Developing contingency plans to adjust production schedules or source materials quickly in case of disruptions.
Reduce environmental impact: AI for sustainability
The factory’s digital twin monitors energy consumption. Data analysis identifies areas for improvement. This allows for:
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Investing in energy-efficient machinery based on recommendations from the digital twin’s analysis of energy usage patterns.
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Optimizing production scheduling to minimize peak energy consumption periods.
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Exploring alternative energy sources like solar or wind power based on data on the factory’s location and energy needs
Now imagine the potential if this factory operates within a supply chain ecosystem together with other parties represented by similar digital twins. Each factory/party leverages a digital twin, a virtual representation of its physical machinery and processes. By orchestrating these parties, and leverage federated data and insights, this can strengthen the overall resilience and efficiency of the supply chain in a significant way. A collaborative approach would foster continuous improvement and pave the way for a more sustainable future for all participants.
Taking the first steps towards predictive manufacturing
The potential of AI in predictive manufacturing is undeniable. Transitioning to this data-driven approach requires careful planning and execution. AI and new tech is not a silver bullet and the necessary groundwork will increase chances of success:
Assess readiness: Conduct a thorough evaluation of your current manufacturing processes, data collection capabilities, and infrastructure. Identify areas where data collection can be improved and invest in necessary sensors and IT systems.
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Set target KPIs: Clearly define your goals for implementing predictive manufacturing. What areas do you want to improve – efficiency, maintenance, sustainability? Establish key performance indicators (KPIs) to track progress towards these goals.
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Craft data strategy: Plan how you will collect, store, and analyze data. Ensure data security and establish a governance framework for responsible data use.
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Build capabilities: Consider hiring data scientists or partnering with AI specialists who can help develop and implement AI models for predictive maintenance, process optimization, and supply chain management.
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Start small and scale: Begin with a pilot project focused on a specific area like predictive maintenance for a single machine or production line. This allows you to test the technology, refine your approach, and demonstrate the value proposition before scaling up across your entire operation.
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Continuous improvement: Predictive manufacturing is an ongoing journey. Regularly evaluate your AI models and data analysis processes to ensure they remain accurate and effective. Be prepared to adapt and refine your approach as your needs and the manufacturing landscape evolve.
In addition, look beyond the boundaries of your own organization. The magic happens when connecting a series of federated model to create a dynamic, data-driven supply-chain.
Algorithma’s digital twin solution for the shipping industry
Author
This article is authored by our strategic partner Algorithma, a pioneering strategy, transformation and AI firm committed to driving business impact through the latest in AI and tech.
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Introduction
Companies on a growth journey often come to a point when taking the decision to set aside time to refine and/or reassess its operating model. Initiating such a program is often associated with multiple challenges but would also bring multiple benefits if successful. Regardless of whether your business model is built on flexibility and tailored solutions or aimed at streamlined operations focusing on efficiency, volume, and cost – a well-oiled operating model is needed and can help your business in the execution part.
To help getting off to a good start and to make sure an operating model program keeps on track, several factors need to be addressed. The complexity and scope of such a task may be daunting. To help power program efficiency and limit the risk of not reaching the desired target, we propose paying extra attention to a number of aspects as listed below.
Laying the Groundwork: Defining Processes, Scope, and Objectives
1. Agree on a high-level process landscape
Without strong agreement on what your company’s key business processes are, there is a high risk of getting stuck in debates on scope, (functional) responsibilities, and overall ambition level with the Operating Model program.
Ensure agreement of scope with key stakeholders early on and assign ownership to each of key process to help make sure key decisions are taken in the work with developing future state. Below is an example on how a high-level process landscape might look like for one company. However, what is considered a supporting process for one company can for another be considered a core business process.
2. Identify and Address Core Pain Points
Understanding and prioritising the real pain points across the organisation is important to ensure that focus is on solving the most pressing questions that help the business see the true value of the work.
Engage with people in the organisation to identify, categorise, and prioritise pain points in appropriate categories (e.g., process, people, IT, governance). Typical pain points within e.g., the travel & expense process in finance, might be a time-consuming process for handling expense receipts, a document intensive process for applying for corporate credit cards and lack of personnel to handle the requests.
3. Tackling High-Impact Areas First: Do not try to solve everything at once
Trying to solve everything (all at once) and not just the most important pain points may probably result in a prolonged and inefficient operating model program and the desired target may not be achieved.
Build your future state by continuously focusing on the true pain points and manage your scope to ensure progress (e.g., in sprints). It is not possible to address all management processes, core business processes and supporting processes at once. If, for example, finance is considered one of the areas with most urgent pain points, it should be addressed first and later pain points within other areas can be addressed.
4. Collaborative Redesign: Involve relevant stakeholders
Cross-company involvement is vital to ensure that the organisation understands what the desired target is and the expectations on them as well as their contribution in capturing current issues that they experience (which would need to be addressed). Change is embraced best when you feel involved.
Make sure to involve people across the business, ensure that there is a combination of functional representation and operations. For instance, when addressing a process such as order to cash, many stakeholders (finance controller, treasury, tax, project manager, etc.) need to be involved as they are all part of the process.
5. Set up a Governance Framework
Inefficiencies and unclarities often come down to issues related to decision-making at various levels in the company. Agree on what key decisions there are, who should take them and when. Avoid bottleneck situations and limit the number of roles involved when possible.
For example, within finance there are many processes and the processes in turn have multiple decision points or approvals. There should be one role responsible for the order to cash process to ensure that the process runs smooth and without bottlenecks. The decision points within the process can have other roles assigned to them, e.g., treasury to decide on funds flow.
Conclusion
In summary, to ensure program efficiency and achieving the target when reassessing the operating model, make sure to agree on a high-level process landscape, find the true pain points, address what is important and do not try to solve everything. Try to involve the business as much as possible, and secure that governance and decision-making are clear in the processes.
At Opticos, our team of experienced management consultants specialize in guiding companies through complex operating model transformations. With our strong background in IT management and business process optimization, we offer tailored solutions to align your strategy, people, processes, technology, and governance for sustainable growth. If you’re embarking on an operating model reassessment, Opticos can be your trusted partner.
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In the fast-paced realm of business, a silent revolution is coming in the form of a digital wave. Digital and Artificial Intelligence (AI) innovations are reshaping the landscape of how organisations operate, unlocking unprecedented efficiency, agility, and strategic insights. Digital technology now touches almost every part of our lives thanks to new technologies like cloud computing and artificial intelligence, along with new ways of building software. As long as technology keeps advancing, your business will need to adapt. So, it’s important to see digital and AI transformation as something ongoing, not just a one-time thing. This journey involves constantly improving competitiveness by quickly adopting new technologies. As technology becomes more important, the difference between business and tech leaders will become less clear. That means all senior executives will need to know how to use technology effectively in their areas.
This substantial increase in spending, clearly suggests that organizations worldwide are increasingly investing in digital transformation initiatives to modernize their operations, improve efficiency, enhance customer experiences, and stay competitive in an increasingly digital world.
In this exploration, let’s shed some light on the ten digital and AI innovations that are reshaping businesses worldwide.
1. Generative AI: Data scientists globally are working on a special part of AI that focuses on making machines creative, like humans. These AI programs, called generative algorithms, can take different kinds of data – like videos, pictures, sounds, or even computer code – and use it to make completely new stuff that has never been seen before. One famous example is GPT-3, made by OpenAI. It can write text that’s so similar to what humans write, you can hardly tell the difference. Another version called DALL-E can even make pictures.
2. Cybersecurity Reinforced by AI: Business leaders worldwide see cyber-attacks as the biggest threat. In today’s world where cyber dangers are growing, using AI for cybersecurity has been a game-changer. AI technology helps to examine large amounts of data to find any unusual activities or possible breaches, making our digital systems stronger against cyber threats.
3. Blockchain beyond cryptocurrencies: Blockchain technology is experiencing dynamic growth beyond its association with cryptocurrencies. While Non-Fungible Tokens have surged in popularity, redefining ownership in digital art and entertainment, decentralized finance (DeFi) platforms are reshaping traditional banking and finance systems. Alongside these trends, blockchain is quietly revolutionizing business operations by enhancing transparency and accountability in areas like supply chain management and secure data sharing. The integration of blockchain with emerging technologies such as artificial intelligence and the Internet of Things (IoT) is further fueling innovation and expanding its applications across various sectors.
4. Augmented Reality (AR): Augmented Reality (AR) is experiencing a dynamic evolution, marked by several key trends. It’s revolutionizing retail with immersive shopping experiences and aiding remote collaboration across industries like manufacturing. In healthcare, AR is enhancing surgical precision and patient care while also transforming education through interactive learning experiences. The emergence of spatial computing, combining AR with AI, promises even more seamless integration of digital content into our physical world. As AR gets better and more popular, it’s going to really change how we do things, learn, and talk with each other in the future.
5. Digital twins transforming industries and reshaping operations – Digital twins are rapidly becoming a key trend across industries, including manufacturing, where they are quietly revolutionizing production processes. By creating virtual replicas of physical assets, businesses can continuously monitor, analyze, and optimize operations in real-time, leading to reduced downtime and enhanced efficiency. Recent advancements in IoT sensors and data analytics have made digital twins more sophisticated, enabling predictive maintenance and AI-driven optimizations. Cloud-based solutions are also gaining prominence, facilitating remote access and collaboration among stakeholders. Moreover, digital twins are finding applications beyond manufacturing, such as in urban planning and smart city initiatives, where they allow authorities to simulate and optimize infrastructure projects before implementation. As digital twin technology continues to evolve, its transformative capabilities are poised to drive innovation and efficiency across various sectors. The digital-twin technology market is projected to experience a rapid annual growth rate of approximately 60 percent over the next five years, culminating in a valuation of $73.5 billion by 2027. Companies have observed a 25 percent reduction in quality issues for products that originate as digital twins before entering production. Furthermore, nearly 75 percent of companies have embraced digital-twin technologies, with many achieving at least medium levels of complexity. Source : “Digital twins: The key to smart product development,” McKinsey, July 31, 2023.
6. Cloud computing for real-time insights: Cloud computing is the very foundation upon which businesses can build their digital transformation initiatives. Its power is its agility, adjusting perfectly to workloads and adapting to the ever-changing markets, new customer demands and trends. With cloud, scaling applications up and down has been super-fast and easy, leading to much more efficient operations and getting your products or services faster to the markets than before. Cloud is the backbone of today’s digital world and base for companies’ digital transformation lift.
7. Big data analytics driving informed decision making: Data has become the very lifeline of every thriving business and is no longer an option. Big data analytics is emerging as a game-changer. By using historical data and advanced algorithms, businesses can use predictive analytics to predict future trends, customer behaviors, and market shifts. This enables informed decision making, minimizing risks and maximizing opportunities. Harnessing the power of big data is the key to surviving in the new age business world and leading the charge with every data driven step.
8. Natural Language Processing (NLP) and AI powered chatbots in customer service: AI-powered chatbots are increasingly being used in the customer service area. These chatbots can be used 24*7 and hence, enable businesses to respond to customer queries faster and in a more consistent way. Using Natural Language Processing in chatbots, businesses can engage in seamless conversations with customers. This innovation transforms customer interactions, providing personalized and efficient services. Overall chatbots have been a game changer in customer service by automating customer support tasks. This has enabled businesses to reduce their costs substantially in this area by automating standard queries and hence, saving time and resources to focus on more critical tasks.
9. Robotic Process Automation (RPA) in business processes: Behind the scenes, robots are taking on repetitive tasks, liberating human resources for more strategic endeavors. RPA is revolutionizing data entry, invoice processing, and other routine tasks, resulting in increased efficiency and cost savings. This is helping businesses to scale their operations more quickly, and alongside, enabling them to take on more employees and transactions without adding more manpower.
10. Explainable AI for Ethical decision making: The increased reliance on AI has resulted in greater accuracy observed by humans. However, the transparency and reasoning behind AI judgments are often more crucial for trust and reliability in both AI and human decision-making. Explainable AI serves as a bridge between humans and AI, offering a set of methods or processes used by AI to arrive at specific conclusions. The emphasis on interpretability to enhance decision-making accuracy is expected to become more pronounced in industries such as healthcare, human resources, and others. With AI becoming more common, it’s crucial that its decisions are ethical. Explainable AI plays a critical role in ensuring transparency and understanding in the decision-making processes of algorithms, thereby mitigating the risks associated with biased or unethical outcomes.
While big news may focus on fancy new technologies, the real change in business happens quietly. These ten digital and AI innovations are like unsung heroes, changing how companies work. They’re making things run better and smarter, while also thinking about what’s right. As businesses keep growing, using these behind-the-scenes changes will be important to stay ahead in the digital world that’s always changing.
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Introduction
As the EU is preparing to transform into a greener future and with new directives being binding for member states, organisations will have to adapt both their daily operations and overall strategy. A holistic approach is important as IT, Purchasing, and Supply Chain Departments will play a critical role in assuring compliance with the new set of policies and initiatives becoming reality within the next years. (Read our article on the EU Green Deal)
This article explores how your organization can navigate the tangled regulatory landscape following the EU Green Deal and introduces you to valuable tools and frameworks to get you started in your sustainability journey.
Traversing the terrain of the EU Green Deal
Going back to 2020, the European Commission approved The European Green Deal which comprises a series of policy measures designed to steer EU on the path to a green transition and achieving climate neutrality by 2050.
One of the centerpieces of EU’s efforts to reach the goals of the Green Deal, is the Eco-design for Sustainable Products Regulation (ESPR) which stipulates the requirements to reach a circular economy. ESPR obliges a Digital Product Passport (DPP) for a vast majority of European market products, aiding consumers in making sustainable choices by scanning QR codes.
The regulation was provisionally approved in December 2023 by the European Parliament and will be gradually implemented until 2030. It will affect both B2B and B2C businesses for most products on the market by requiring sustainability data across the value chain in the product passport. It also offers recycling guidance for secondhand transactions.
In parallel, in March this year the CSDD (Corporate Sustainability Due Diligence) was also provisionally approved and in January 2023 CSRD (Corporate Sustainability Reporting Directive) came into force. Together, they are the foundation for stipulating the importance of corporate responsibility and sustainability in business operations, particularly focusing on supply chain sustainability. The CSDD will obligate businesses to incorporate both sustainable social- and environmental elements into their operations. The overarching goal is to guarantee that corporations commit to and take responsibility for their economic, environmental, and social impacts. It will be of particular importance to ensure compliance in the whole supply chain including the sub-suppliers.
CSDD will be implemented in multiple phases starting with large-sized corporations inside the European Union as stated down below:
CSDD is closely related to the CSRD, which aims to replace and improve the existing NFRD (Non-Financial Reporting Directive). CSRD will increase the scope of NFRD to a larger extent of corporations, including publicly listed and large private corporations as stated below:
CSRD requires corporations to report on environmental, social, and governance (ESG) aspects per ESRS standards. The directive will require a number of actions including (but not limited to): Publicly reporting on efforts to address risk related to ESG, taking responsibility for upstream and downstream supply chains, performing double materiality assessment, and conducting third-party audits by accredited auditors.
In summary, the EU is expecting corporations to adhere to and report on a large set of targets related to sustainability to reach the 2050 goals of climate neutrality. In the next sections, we will walk you through how your organization can be prepared.
Sustainability regulations from a Sourcing perspective
Clearly, the EU Green Deal initiatives are steering corporations to increase both strategic and operational sustainability efforts. With organizations being forced to disclose ESG impact and monitor activities regularly to reduce and remedy any environmental or social harm; sourcing will play a crucial role. At Opticos we have curated a “Sustainable Sourcing Approach” to help Sourcing departments aid their organizations in their compliance work by the following three pillars: Ensuring transparency, executing due diligence-focused outcomes, and Enhancing sustainability as a “way of working”.
Opticos Triple Sustainable Sourcing Approach
Along with ensuring compliance with the new regulations throughout your sourcing processes, Opticos supports and empowers your company to proactively embrace sustainability throughout your organization. We help you align your sourcing strategy with the environmental and social sustainability obligations that come with the new legislation and help your organization reach its sustainability objectives.
Complementing the triple approach, Opticos has identified a multitude of activities, guiding the way to Sustainable Sourcing, together outlining a framework that can help your sourcing department adhere to the due diligence activities.
In the Sustainable Sourcing framework, two critical perspectives of sourcing activities come into play: Sustainability Compliance and Corporate Sustainability Target activities. The former is a reactive approach, focusing on adhering to legal requirements. The latter, a more proactive approach, goes beyond mere compliance. It involves investing in sustainability as a value for your company, striving for excellence rather than solely meeting obligations. By adopting our framework, your Sourcing department can achieve compliance while maintaining a forward-thinking, proactive approach.
Opticos Sustainable Supply Chain Assessment
The new regulations stemming from the EU highlights the importance of transparency and accountability in the entire value chain. The supply chain departments must thus comprehend the expectations set forth and acknowledge the important role they play in this context.
An initial supply chain assessment can provide valuable insights as well as form a baseline for evaluating the current state of supply chain sustainability readiness and maturity. In addition, identifying and recognizing critical elements can help shape dedicated actions, or as a minimum, a firm understanding of the organizations risk profile supporting the relevant initiatives onward.
Exhibit 2 below displays Opticos framework for ESG assessment from a Supply Chain perspective with a focus on Environment, Social, and Governance.
“By following the framework with the set processes, your Supply Chain organization can remedy risks of not adhering to the EU sustainability acts” – Anders Gullbrandson, Co-founder, and Chief Legal Officer at Opticos.
Simultaneously your organization can progress to greater monitoring and predictability of your suppliers by following the regulations. (Also read: Leveraging IT to achieve Environmental Sustainability Objectives)
The Importance of Digital Product Passport IT Assessment
As stated, the EU mandates a Digital Product Passport (DPP) for the majority of European market products, supporting consumers in making sustainable choices by scanning a QR code. In this chapter, we will cover how the Digital Product Passport is set up and how your organization best utilizes it.
The digital product passport is an electronic record of a product that is stored in a database and accessible throughout the product’s life cycle. The product should have a link, as per present technology a QR code, to its passport database printed on it ensuring transparency and knowledge transfer to empower customers to make informed and green choices.
Opticos has designed an IT Assessment framework for the new Digital Product Passport, guiding how organizations can fulfil the requirements and be prepared for the ESPR regulation.
The Digital Product Passport IT Assessment covers four critical phases, defining the target setup, evaluating the existing setup, identifying gaps, and culminating with a roadmap for seamless compliance with the Eco-design for Sustainable Products (ESPR) Regulation and Digital Product Passport (DPP) requirements.
Beyond mere compliance, conducting the assessment assists in optimizing processes, increasing transparency, and enhancing data management ensuing in valuable insights for your organization.
Conclusion
At Opticos, we believe that Sustainability needs to be at the core of any organizations business strategy, moving beyond the legal and reactive compliance approach to regulations. Our best practices and extensive experience in this area can augment your IT, Procurement and Supply Chain departments to successfully transition into these new ways of working in conformity with the EU regulations.
Irrespective of where you are in your sustainability journey, Opticos can add value in terms of advice, domain expertise, Green Deal adapted processes, Master data knowledge or introducing ways to increase transparency in your existing processes.
In this article, we have showcased three practical ways of preparing you to not only be compliant with the new sustainability EU legislation but also how to proactively approach it and use sustainability as a business advantage.
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Thimmy Bernvåg & Anders Gullbrandson
Contributors:
Nils Andersson, Agnes Lundvall, Tobias Nilsson and Sofia Gudmundsson
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Introduction:
What if there was one place where you could go to get all the data you need? No matter what kind of data you are looking for you will find it in this place. It could be your company’s master data, transactional data, analytics data, IoT data or even a document or a video. Sure, you will need to authenticate yourself and have the rights to access the data, but if that’s the case, then you just need to look for it in one place. And best of all, you could rely on the data being presented in this place to be accurate. Like a bedspread wrapped over all your data assets giving shelter and at the same time providing a common interface to the surrounding world. Wouldn’t that be wonderful? Well, that is the main idea behind the concept of “Data Fabric”.
What is Data Fabric?
Data Fabric as a concept has been developing during the past years as an answer to the increasing challenge of getting full benefits out of enterprise-wide data where:
- Companies are consuming IT services provided by multiple cloud platforms like AWS, Azure, GCP and of course, are using different SaaS more frequently.
- The amount of data generated by IoT, apps and social media is exploding.
- More evolving business models depend on the ability to have easy access to data and share more data with end consumers.
- End consumers evaluate products and services by the attached digital services as a key differentiator in their final selection.
- Data regulations like GDPR, DPP and AI-act are focusing on what specific data companies should share with regulating authorities and end consumers.
- Many companies still struggle with data in silos and locked-in legacy systems.
The ideas behind Data Fabric have been in development for many years. It started with collecting data in data warehouses, data lakes and BI platforms and was further developed by adding integration, security, data lineage and master data aspects. In the beginning, this was branded as Enterprise Information hubs or sometimes even as API platforms, but that was unfortunately driven by software vendors who had a hard time delivering upon their promises. So, the more general architectural pattern of Data Fabric was born, though the definition is somewhat blurry and depends on who you ask.
The figure below shows a conceptual architecture of the data fabric concept in relationship to other established concepts.
Fig 1: Conceptual architecture of the data fabric concept in relationship to other established concepts
For example, the exhibit below gives an interpretation of how different vendors in this area define Data Fabric:
Table 1: Interpretation of Data Fabric by different vendors
As evidenced by the diverse interpretations provided in the table above, gaining a comprehensive understanding of the concept of Data Fabric is not straightforward, as it involves multiple perspectives from various sources and vendors. However, analyzing existing discussions surrounding the definition of a Data Fabric reveals a consensus that it serves as a mechanism for generating data pipelines and integrations from diverse sources within a unified platform. However, there are divergent views on whether a Data Fabric is considered an architecture or a broader concept encompassing various technologies and architectures.
Furthermore, when it comes to looking at what creates a Data Fabric, some of the suggestions are pushing the idea that the Data Fabric is based around metadata and metadata analysis. In a metadata-based driven Data Fabric, metadata is used through activation and is then pushed towards the users when creating pipelines but is also suggesting new metadata when data is created from external sources. The metadata would also be enriched with semantics, putting meaning and context to the metadata through knowledge graphs. On these knowledge graphs, it would be possible to apply artificial intelligence and machine learning, and then we have achieved the concept of active metadata. The active metadata feature is considered one of the key features in achieving a Data Fabric architecture, which is analyzed using semantics, knowledge graphs, artificial intelligence, and machine learning.
There are a few contrasting views of how Data Fabric is defined by market participants. While some call it a design concept which could be interpreted as architecture. Then there are others who view the data fabric as a ‘Solution’, thereby interpreting it as an instantiated architecture. Interestingly, most market participants agree that Data Management should be an integral part of the Data Fabric definition, however one goes as far as viewing data fabric as a data management approach which is a broad view which leaves a lot of room for own interpretations.
What challenges are the Data Fabric envisioned to solve?
One of the challenges in organizations is the diversity of sources and systems dealing with data. Data is generated at an increasing pace with the development of new technologies, regulations, and business needs. An increase in data volumes and number of data sources will make the landscape more complex and finding the right data, and understanding the data in context will therefore become more difficult. Additionally, with different systems and user groups, it is not unusual that data becomes siloed. Each system or user group will have access to and understand the data within their respective silos. However, their knowledge about data outside of their organizational unit will be limited.
In addition, this may also lead to difficulties in harmonizing data and establishing consistent data categorization across the organization. Instances may arise where identical data objects exist in multiple locations but with varying identification formats, or worse, different taxonomies. A prime example of this is product or customer information, which may be scattered across numerous systems and often lacks consistency or sometimes, may even present contradictory information.
Another common problem is that the depth of the data architecture needed is underestimated. Large companies tend to strive to simplify the complexity of their own operations to be able to achieve a higher degree of freedom in their business processes. Consequently, processes are not adequately documented, and data is not captured and stored with the requisite granularity and quality. When these companies are faced with higher requirements on data quality by external parties like end-customers, regulating authorities or business partners, it could be a painful wake-up call. Attempting to implement a better order in the base data of a fully operating business is comparable to performing engine repairs on an airplane while it is airborne. Frequently, the solution involves implementing a new IT platform, such as a more robust ERP or master data platform. This enables the enhancement of data quality to coincide with the implementation of the new platform.
Yet another problem is simplifying data architecture work by putting it in the hands of large commercially available off-the-shelf platforms. To avoid tedious data management work, organizations rely on the data architecture presented to them by large solution platforms. The argumentation is that these platforms have many kinds of customers and hence they probably have already thought all data architecture aspects through anyhow. Later it’s not uncommon that these organizations discover the hard way that the complexity of their own business does not fit into this architecture. Then, costly adjustments are made to the solution platforms, data lakes are installed to bridge the gaps and analytical tools are installed to try to understand the data. If these mistakes are repeated frequently across the organization, the final situation will be characterized by disorder and disintegration. Data Fabric has been presented as the cure for these problems, but the question managers should ask themselves is:
Will a Data Fabric really solve the problems, or will it rather attempt to minimize the damage done?
Well, a Data Fabric focused on connecting all data in a business in an easy achievable platform in one place will mostly focus on damage control. To increase the data quality and reliability it is not enough to just connect the data with the surroundings. Here is where a structured approach to cleansing, normalizing, and analyzing the data on the fly can make a real difference. However, even if we could attain a higher level of data quality by incorporating capabilities for “on-the-fly-data-quality-improvement” such as AI, active metadata, and machine learning, it’s essential to maintain a skeptical approach regarding the reliability of the output. Data-driven decision-making assumes that the data is as accurate as possible. However, would you trust entirely machine-generated data to make critical decisions?
Given this rationale, it’s probable that Data Fabric architectures will initially see implementations in domains characterized by high-volume public data flows. In these contexts, data can be interpreted and acted upon with a lower risk of serious consequences in the event of faulty actions. However, as algorithms improve, Data Fabric architectures are likely to ascend in the value chain, eventually becoming a substantial data source in executive decision-making.
Another common problem is to establish and operate a working data governance organization. Many consider working with data governance to be a tedious and time-consuming task that often does not receive adequate attention. Furthermore, even when prioritized, it is frequently assigned to individuals with limited understanding of the potential business consequences of poor or inaccurate data. By implementing a sophisticated Data Fabric Architecture some of the problems generated by poor data governance could potentially also be addressed by establishing a self-healing active metadata architecture. While it may seem utopian at this moment, accomplishing this feat would yield significant potential.
What Data Fabric related technologies are there on the market?
When it comes to technologies related to Data Fabric, these can be classified into different categories:
- To start with, there are metadata technologies, such as data catalogs. Providers of data catalogs, such as Atlan and Informatica, tend to view metadata as a central part of the Data Fabric. These companies also seem to have come the farthest in AI capabilities related to Data Fabrics.
- Other companies like TIBCO, IBM and Microsoft tend to view data pipeline platforms or data integration platforms as central to Data Fabrics.
- Companies like Denodo and Cloudera which have a legacy in data virtualization over several cloud platforms provide offerings that tackle the issue by handling data across multi-cloud environments.
Not surprisingly the different vendors tend to accommodate the Data Fabric concepts as much as possible into their own domains. In the table below we highlight some of the vendors in this domain and their current offerings in the Data Fabric area.
Table 2: Offerings of different vendors in Data Fabric area
How, and to what extent, do these technologies address the challenges above?
Depending on how we view Data Fabrics, and what we need to get out of them, we could look at the following three components:
- A data discovery part, which in essence means a metadata model which can push information to the user.
- A data pipelining/integration part, where data is pulled from the source system and prepared and served to the user that needs the data.
- An active metadata part, where the organization might cater and compensate for some of the worst data quality issues in the underlying data by actively and virtually create the metadata from inbound data instead of matching inbound data against static metadata in the background.
However, merely focusing on data discovery and automation for data pipelines would only address part of the issue as outlined earlier. The common perspective is that a Data Fabric platform should encompass data discovery, data catalog, and hybrid integration tools to effectively tackle these challenges.
Some experts offer AI capabilities to achieve the active metadata setup and argue that without this, it cannot really be considered a Data Fabric platform. The main argument is that if we are aware of which data assets exist and what level of quality those data assets hold, then we can address data quality issues in real-time using AI and machine learning to provide a shield of automated data improvements that will result in improved quality compared to the underlying sources. Nevertheless, to make decisions based on this aggregated data, you must have a high level of trust in your algorithms.
Working with metadata has traditionally been a time-consuming and relatively static process, involving the analysis of required attributes and characteristics of data objects. However, in the future, advancements in technology could enable machines to interpret metadata dynamically, analyzing input data and utilizing AI algorithms to meta-tag data based on similarities with previous instances. This would undoubtedly represent a paradigm shift in data interpretation, capture, and analytics, unlocking the potential for advanced data handling in a fraction of the time compared to current methods.
Some providers are also taking this one step further and are integrating AI tools to create a spoken natural language interface to the data discovery module making the data even more accessible.
What do we see as challenges with Data Fabric?
Implementing a seamless data layer on top of a large and scattered data landscape brings its fair share of challenges. It is likely that organizations with complex IT/data landscapes will be those with the most to gain from investing in a Data Fabric architecture. On the other hand, the implementation of such a fabric project could be an arduous and time-consuming process, increasing the possibility of failure.
While legacy issues such as data accessibility and presenting the data in a consumer-friendly format remain, modern hybrid platforms have the tools built-in to address them.
If a company has successfully implemented technologies for data access and publication, the primary challenge moving forward will be ensuring the trustworthiness of the outcomes. It is tempting to think that an enterprise’s common Data Fabric is seen as a cure for the bad underlying structure. What you achieve by implementing a Data Fabric on top of this mess is that you get a centralized mess where you easily can access the underlying bad data. This makes the poor data quality more visible rather than being restricted to a backbone legacy environment, translating into business decisions likely being taken based on incorrect data!
So, the real concern will be around data quality. The most effective approach to addressing this concern is by improving data quality at the source through processes such as data cleansing and enrichment. Further, an understanding of metadata and data structures will be required. AI can assist in automating manual and time-consuming tasks, not only in tidying up data sources but also during real-time data consumption.
What are our conclusions and recommendations?
To summarise, we feel the following observations are note-worthy:
- Consider Data Fabric to be an architecture rather than a tool.
- Currently, we do not observe any vendor in the market offering a comprehensive tool or platform for building a Data Fabric architecture. However, several vendors provide platforms and tools that could serve as essential components of your overall Data Fabric architecture.
- Investing in a Data Fabric architecture must be seen as a research proposition where parts of the investment can be attributed to building knowledge and gaining experience. Prepare for the need to replace components in your architecture later, as the technologies mature.
Data Fabric architecture will find its first successful and cost-saving implementations in organizations with a high volume of data exchange with the external world and where the quality level of the data exchange is not critical. For example, the distribution of reviews on hotels, products and restaurants to many different sites and platforms.
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Hans Bergström, Mattias Gustrin & Eric Wallhoff
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Introduction
In today’s rapidly evolving digital landscape, IT and technology have become pivotal to business success and as a result, navigating IT investments has become a critical challenge for modern organizations. Aligning these investments with business strategy has become not just a necessity but a strategic imperative to ensure that each investment not only supports but also drives strategic objectives.
Furthermore, funding from continuous improvements and operational excellence initiatives driven within the business or IT organization are often expected to drive out cost, releasing funds that can be used for transformation and change rather than operation.
In this article, we will present an introductory overview of the Opticos model, designed to address these key challenges. The model assists organizations in adopting a value governance approach for IT investments. The aim of the model is to create a comprehensive model that supports the reader in connecting tangible business values to IT investments ensuring a clear connection between technology initiatives and business strategy. This alignment is crucial for realizing the full potential of IT in driving business success.
We’ll explore how the Opticos model facilitates this alignment, transforming IT investments into strategic assets that propel organizational growth and operational excellence.
The Opticos Model
The Opticos model is an evolution from common concepts addressing areas such as value governance, portfolio and investment management, and business impact value tracking, in combination with customer assignment experiences.
Opticos has built its service offering and advisory around the three-step approach and the four key dimensions. The foundation of the model is depicted in a three-step approach that when done right will ensure that IT investments within an organization will always support the strategic objectives of the business, and by so doing ensure the realization of business values. The four key dimensions are interconnected and essential to drive business value by identifying and prioritizing what IT investments will support the business the best based on its priorities. Both these concepts will briefly be introduced in the following.
The three-step approach
The three-step approach can be used regardless of operating models or organizational design. However, it is important to keep in mind that to navigate through these steps, different tools need to be used to successfully implement the model, and that the tools are chosen with regard to organizational procedures and existing governance.
What the three-step approach offers is a structural approach to aligning IT investments with business strategy and ensuring that each investment has been approved and that it is providing the value that was intended by value tracking through the entirety of an investment’s lifecycle.
1. Business strategy change implies that each organization’s business strategy normally contains elements where change initiatives have been identified as required for the strategy to materialize and be achieved
2. Strategic objectives define the requirements for executing the identified changes into a select number of objectives that can be further detailed and prioritized. These objectives can put focus on any function or area within the organization such as HR, Sales, Supply, R&D, ESG, etc.
3. Business capability mapping breaks down the strategic objectives from a business capability perspective, and by doing so, also provides the foundation for what IT needs are required to secure the business capabilities at an enterprise
4. Investment domains define the specific IT requirements at a platform or solution level, closely aligning with the conceptual mapping of business processes. This approach ensures that the IT investments support the operational and strategic needs of the business
5. Investment management is where the investment domains within IT have been converted into specific IT solutions, platforms, domains or transformation activities that will support the strategic objectives to materialize and subsequently enable the business strategy to be fulfilled.
At this stage, identified change initiatives have been converted into programs or projects that need to be priced in order to be prioritized. To facilitate this, an initial business case is typically required. This business case should originate from the originally envisioned business benefits and expected value outcomes.
6. Value tracking is needed during the entire lifecycle of each investment in order to ensure that the expected values identified and showcased in the approved business cases are realized. For this, clear ownership and metrics are key
Four dimensions
The four dimensions can be used to manage IT-driven change where IT is leveraged or required to fulfil the business strategy and the expected values. The tool can be used as an end-to-end process to ensure value realization as well as a tool to transform the current IT organization focusing on operational efficiency and the release of IT funding that can be used for transformation instead of operations.
DEFINE – The desired outcome of the business strategy provides guidance for how funding should be allocated to ensure that the expected business values can be realized. To ensure the right focus, the three-step approach can be used to convert the business strategy into tangible strategic objectives, and business capabilities that are easily mapped to enablement and requirements within IT
TRANSFORM – Focuses on achieving operational excellence and cost optimization within both the business and the IT organization. Traditionally, standardization, consolidation, and sunsetting of the current IT landscape contributes to release funding by lowering operational cost that can be used for change initiatives requested by the business
INVEST – This dimension is the culmination of DEFINE and TRANSFORM where available funding is distributed to IT investments that contribute to fulfilling the business strategy and the strategic objectives set by the business. By doing so, IT investments will only be realized where tangible values have been identified that in a cohesive way can be measured and tracked
TRACK – Focuses on accountability and responsibility for the investment, business case ownership, and tracking value realization over the entire lifecycle of the investment. It is not uncommon for organizations to focus on the project phase and take control over project execution, capitalization, and cash flow, but lose themselves in the actual operational phase of the outcome from the investment in question.
It is important to, for instance, reflect over: “Did we manage to automate the intended processes so that x number of FTEs could be used elsewhere? Did we manage to decrease our storage footprint by consolidating and lifting local storages to the cloud and applying active management of the solution?” just to give a few examples. Securing the full potential of value realization is only possible by adopting a lifecycle perspective
Putting it together
Jointly, the three-step approach and the four dimensions offer a powerful toolset that can be used to align IT investments with the business strategy where transformation requirements are driven or leveraged through IT and new technologies. While the three-step approach addresses how the business strategy in a structured way manifests itself in IT investments, measured and prioritized by business value, the four dimensions put the realization of the business strategy in an IT strategic and operational perspective.
Given the output from the three-step approach, how should IT (and the business) distribute its funding given current operational requirements and future transformation expectations? How should the IT organization balance funding of its own service portfolio to the portfolio of investment, e.g. portfolio, program, and project management, and how should the expected and realized values be quantified, prioritized, and tracked? With the Opticos model, the users can choose to apply the whole model as well as cherry-picking relevant or prioritized parts. The model can be used as a toolbox of governance activities and metrics as well as a means to build understanding and collaboration between IT and the business.
Summary
Organizations of today need to ensure that IT investments are made based on what business values they will contribute to realizing. Strategic objectives of the business strategy need to be linked to business capabilities, processes and supporting IT solutions. With limited funding, only investments in IT that contribute to fulfilling strategic objectives should be approved and prioritized. To raise and enable funding, many organizations need to optimize and streamline their current business and IT operations, often through digital transformation or automation, consolidation, and modernization.
Regardless of where you are in your business transformation journey, scaling and leveraging new technologies and IT to become more competitive, more innovative, or more agile, Opticos can help you ensure that your IT investment portfolio is governed, tracked, and aligned towards your long-term strategic objectives of your business.
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In today’s business environment, even traditional mid-market organizations have become global enterprises. More and more companies are implementing a global ERP to drive optimization and integrate data and information across multiple countries into connected applications. Developing and maintaining a global ERP solution comes with its own set of challenges – but with the right ERP strategy, companies can navigate through the barriers to meet their objectives.
For any organization, the typical goals of a global ERP Implementation can be as below:
- Standardized business processes on a global level
- Improved data quality and consolidated reporting
- Simplification of the IT landscape and reduction in operating costs
Before embarking on the ERP implementation journey, organizations need to have a clear vision of where they are and where they want to be. It is a huge transformation effort and involves significant changes to business processes, technologies, and culture. The success of the implementation does not solely depend on the technical aspects. It also requires detailed attention towards organizational change management.
The ERP universe is ever-expanding, but ERPs can only deliver results when the fundamentals are in place. An executable strategy can maximize your return on investment and set your organization up for long-term success.
ERP Strategy
A pre-study or a conceptual phase is often carried out to prepare for a large-scale ERP implementation exercise. In our experience, a conceptual phase can help in defining the scope, goals and expected outcome that can be communicated to all the internal and external stakeholders. Some outcomes are as follows:
- Clear vision and blueprint of business needs, alignment of all stakeholders
- Final scope, time plan and roadmap for the implementation exercise
- Program Methodology, Governance and Team Structure
- Sourcing Principles and Strategy
- Data Strategy and Key Design Decisions
1. Sourcing Strategy
ERP programs are often very large investments for organizations and are associated with operational and financial risk and are a driver for major change. That is why it is essential to form a solid strategy for sourcing an ERP implementation partner(s) early on. There are many factors to look at – for instance, make versus buy strategy, pricing model, sourcing objects, supplier capacity, and capabilities to engage the right partner(s) in a timely manner and to help deliver on the transformation objectives.
These areas are generally part of an ERP Implementation Partner Sourcing Strategy:
- Strategic Drivers or Business Value
- Sourcing Direction (Sourcing Objects, Supplier Selection, Make or Buy decision)
- Application Maintenance and Support Services
- Program Governance
- Commercial Engagement Model
To know more, you check our article here.
2. Data and Reporting Strategy
Today, many organizations are flooded with data and are looking for better ways to develop real time reports and insights. Technologies are often implemented without yielding the envisioned results and become overly complex to maintain. Why? To put it simply, it’s the lack of an overall data and reporting strategy to integrate, synchronize and govern. What’s more, while companies are inundated with data, much of that data is in disparate, non-integrated systems. Master data can be all over the map in global organizations with layers of different ERP systems. For multinational enterprises, this issue is further amplified by the number of subsidiaries.
A robust data and reporting strategy – focused on clean, consistent, and well-defined data – can assist companies to drive growth and overall competitiveness. To build a successful ERP data and reporting strategy, companies must start by accounting for different stakeholders across the organization.
Fig 1: Data & Reporting requirements of Stakeholders involved
Program Methodology:
ERP implementations are often multi-year initiatives that involve significant capital investments, long-term planning, and business process re-engineering. The implementation approach you select for your company must fit your company’s complexity and culture to maximize the chances of a successful implementation.
Many companies try to derive the best values out of different methodologies to identify a best fit for their organization. For instance, a waterfall approach can provide good structure and milestones which can then be combined with agile within each phase to iteratively create the phase deliverables. It is always a good practice to maintain an MVP mindset and try to get user feedback as early and frequently as possible.
- Fit To Standard:
Organizations now view ERP as a backbone for their operations. ‘Fit to Standard’ is hardly a new concept but there is a renewed focus on it as companies strive to reduce cost of ownership, implement best practices and create a clean core solution. A stable core is essential as it is relatively easy to add niche capabilities on top.
A Business change impact assessment, while building the strategy, can assist organizations to study existing processes and identify what they can or cannot live without. If needed, only the truly essential processes should be customized. This can give organizations a better control over their IT landscape and make way for easier governance.
- Global Template:
When you finally make the decision to implement an ERP solution, there comes a point when you need to decide whether deploying a global ERP template across multiple sites, divisions, and regions is worth it. The answer to this question can drive the overall strategy of design, development, and deployment decisions along with the long-term support services going forward.
International organizations often have non-standardized business processes and deciding to implement a global ERP system across any enterprise is not easy. For one, the decision to globalize or localize isn’t black and white. While standardization allows to scale for growth by consolidating business processes and driving operational efficiency, organizations also need the flexibility to serve diverse customers, employees, economies, and regulatory bodies. Striking the right balance between standardization and flexibility thus becomes essential. To know more on this, you can read our article here.
Figure 2: Risk for Global Template Rollout
Program Management and Governance
Any ERP implementation is a complex and costly undertaking that requires careful planning, execution, and monitoring. Project management and Governance are thus key factors that can determine the success or failure of an ERP implementation. With global implementations, the complexity for the program management teams is higher as several projects run in parallel across different regions. Additionally, there may be several implementation partners working simultaneously leading to multiple participants and a need for an even better coordination. Organizations, thus need to have a set of governing principles that help them define the PMO teams and structure.
A key aspect of ERP project management and governance is to monitor and control the progress and performance of the project. Organizations need to use appropriate tools and techniques, such as dashboards, reports, meetings, and feedback to monitor and control the project. PMO needs to track and measure the key performance indicators (KPIs) and milestones of the project and compare them with the baseline and expectations and communicate it with all stakeholders – internal or external.
Another critical aspect of ERP project management and governance is to ensure the quality and testing of the ERP system. You need to verify and validate that the system meets the functional and non-functional requirements and complies with the standards and regulations. It is important to involve the end-users, business owners, and vendors in the testing process, and document and resolve any defects or issues.
Change Management is Critical
Human factors like organizational behaviour and training are often ignored but are just as crucial to a successful ERP implementation as addressing technological requirements. Local entities may be extremely resistant to globalized processes. They need to understand the reasons for transformation and how it will personally benefit them.
It’s important to create a communication plan that addresses how, when, and where you’ll communicate key updates. This includes adjusting your messages as required to accommodate different languages, cultures, and time zones. Communication is just one part of organizational change management.
A plan at the local and global levels is needed to ensure your organization is prepared for a global ERP rollout. Without properly training employees across headquarters and local establishments, it is nearly impossible for a global ERP rollout to occur smoothly.
Throughout the ERP programme, change management needs to ensure that organizations, leadership, and employees are:
- Clear on how the change will impact the existing ways of working
- Aware of why the change is needed and what are the benefits of change
- Ready, willing, and able to implement change
Application Management Services
Creating or implementing an ERP is not the end and organizations need specific expertise, robust operating methods and tools that seamlessly enable work across a global team environment. Decisions around AMS can have a profound impact on the total cost of ownership, user satisfaction, solution agility and ultimately the success or failure of the ERP solution.
Organizations should look to prioritize AMS while developing the ERP sourcing strategy and evaluate the benefits of different available options – Developing an in-house team, using an external supplier or a combination of the two.
Guiding you through your Organizational Change Journey
A global ERP implementation is not just a technical IT project but a huge change effort. It is an organizational journey leading to new ways of working. Organizations therefore need to create a business change program and mobilize a team to focus on communication and change strategy.
While you may want to rush into it to maintain a competitive advantage or keep up with shifts in customer demand, it is important to ensure your business is prepared for this endeavour. The key is to create a balance between central and local requirements, prioritize communication, and strategize the rollout.
Drawing from our extensive client experience and proven methodologies, we can guide your organizational journey from strategy to implementation and support.
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How will your company’s business look like in a world that is influenced by AI? Do you consider technological shifts imposed by AI as transformative or disruptive for your industry and business? This article will provide you with a general framework and some practical recommendations on how to get started with mapping the technological impact of AI and start crafting your AI journey.
How does your company address the technological shift imposed by AI?
Perhaps, you see AI as a subset of the advanced analytics domain and have a team of highly skilled professionals working on developing algorithms for business needs. Maybe, your vision of AI’s role at your company is similar to autopilot systems in airplanes which manage a slew of routine tasks so pilots can focus on essential decision-making. Perhaps, you have just started conversations on AI topics within your technical or business teams. Regardless of where you are in your AI journey, this is the right time to employ a structured approach to managing the impact of AI technology at your company. While integration of AI into your business processes may seem complex, there are a few simple things you can do to get started.
AI is an umbrella term for several technologies, methods, and their combinations that in one way or another, attempt to replicate aspects of human intelligence. One of the technologies is Machine Learning (ML), which is primarily useful for data analytics and predictive modeling. Companies use it to forecast sales, manage inventory, and detect fraud. Another common AI method is Natural Language Processing (NLP), which powers chatbots and customer service automation. We also see AI in the form of robotics that streamline manufacturing processes. Recent advancements in the field of generative AI such as ChatGPT and Midjourney have made it possible for everyone to see AI in a new, content creator role.
One of the first actions you might take in the beginning of your AI journey is to initiate a process for formulating the organization-wide AI strategy. It will enable you to think about your goals with AI and create a high-level action plan for achieving these goals. A good strategy will build a common understanding of what the main principles for the expansion of AI at your organization are and, importantly, what you have chosen not to do. The whole purpose of AI strategy should be to provide a formula to align all AI projects and activities with business capabilities and value creation in the organization.
Here are some recommendations for how to make your strategy more actionable:
1. Get yourself acquainted with AI
Understand what it is capable of and assess its relevance for your business in the short and long term. You could allocate a team within your innovation department or cross-functional, engage vendors to provide ideas, organize an ideation workshop such as a Hackathon with experts to help you map your ideas to available technologies. The choice you make will depend on your organization’s size, industry, culture, availability of resources and skills, budget and other factors.
2. Set a time plan for your AI initiatives
Define the time horizon for your strategic goals. Do not look too far in the future. As there is little evidence that AI will outperform humans in all aspects of intelligence in the next ten years, you do not need to focus too much on how the world will look like then. Instead, put your efforts into exploring how AI can improve your business and consider the following phases.
Figure 1: Example of an AI roadmap
3. Focus on areas that can make an immediate impact on your business
For example, you could consider the impact of AI technology in the following areas:
3.1. Improving operational efficiency and reduce costs: AI as a productivity tool
Operational efficiency focuses on means to reach business goals and productivity. AI will not replace humans, but humans not using AI in their work will be replaced by humans using AI. The choice of use cases will depend on type of tasks that are being performed by your employees. If customer service is an important part of your business, then AI-powered automation presents tremendous efficiency gains and relatively low risks. If you develop software internally, consider using AI-powered programming co-pilot to accelerate delivery of features and bug fixes. Test your AI innovation ideas here first. Showcase the success stories and lessons learned to inform decisions regarding upcoming AI projects. For example, Morgan Stanley Wealth Management deployed generative AI to power an internal chatbot that streamlines access to their extensive knowledge base, providing advisors with instant access to expert-level knowledge.
The main idea of AI as a productivity tool is do the old thing with a new tool. So, look for tasks that you can outsource to AI.
3.2. Launch new business lines and products: AI and business development
Your company’s competitive strategy was formulated in an environment with certain industry opportunities and threats as well as broader societal expectations. Changes in this environment, driven by AI advancements, could be so substantial that you will need to re-visit your offering. For example, a clothing brand could utilize a personalized recommendation engine together with an AI-powered chatbot to deliver a styling advice to its customers. If your company offers knowledge-intensive products and services such as risk advisory, you might find a business case in leveraging AI to deliver analytics in real time instead of static reports.
Use the knowledge obtained from your first AI projects where AI was used as a productivity tool. Now it is time to do the new thing with a new tool. What new customer needs can be met by AI-powered products and services? How should you combine human-centric and AI elements to stay competitive, attract talent and improve your position on the market?
3.3. Become familiar with AI risks: create foundation for AI governance.
AI is already regulated in several geographies and more extensive regulations such as European AI Act are on the way. In addition to regulations there are ethical considerations that could be used as a guidance for AI governance. If you are in the beginning of your AI journey, make it a responsible AI journey from the start. The guardrails will pave the way for trust in AI, address the common fears and encourage use of AI in your business.
Figure 2: One of the basic purposes of AI governance is to enable responsible AI
The three steps above provide you with a good ground to stand on when formulating and executing your initial AI strategy.
Final notes
AI awareness program
An AI awareness program is a good way to take lead in AI area and create common standards. If AI will have an impact on organizational culture, the awareness program is a way to soft start this shift.
Cross-functional cooperation to enable AI
Successful integration and use of AI in your business is not a tribute to a particular function, but rather result of collective efforts of several functions, including so-called AI enablers such as Digital, Data, Ethics, Legal and Business process owners.
Democratization of AI
There are several signs of AI becoming an integral part of our work and existence. If democratization of AI is what the future holds, it might be relevant to prepare your organization for new processes involving decentralized decision making, increased role of citizen data scientists and relevant data governance practices.
At Opticos, we enable organizations to leverage the business benefits of new emerging technologies. Drawing from our extensive client experience and methodology in business strategy, change management, data management and AI governance, we’re here to support you in your AI journey from strategy to implementation.
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All organizations are required to carefully manage information security to survive in an era of complex threats and repeatedly large security breaches for all types of organizations, for instance, T-Mobile, The Swedish Transport Agency, and LinkedIn. But how does your organization know how secure is secure enough? How much should we spend on security?
In an increasingly digitalized business world and with a sharp increase in cybersecurity spending across the board, ensuring confidentiality, integrity, and availability for your organization’s information and IT systems is, in many cases, becoming a major issue not only for CIOs and CISOs but for the entire C-suite. It is a complex challenge to strike the correct balance between, on the one hand, security and, on the other, sound investments and resource allocation.
Investments and initiatives within cybersecurity and information security should be proactive, ensuring the possibility of being responsive and optimise security spending. Through the introduction of different types of security measures, we decrease our exposure and avoid disturbances and even severe incidents and attacks with tangible financial impact. These measures could, for example, include security audits, vulnerability assessments, employee training, regular software patching, and so on.
While these investments are crucial for minimizing risk, they all have a cost associated with them. With the inherent proactive nature of these types of security investments, determining how much to invest is particularly difficult, as the benefits or Return on Investment (ROI) may be challenging to track and quantify with traditional monetary metrics, as you would, for example, for advertisement spend.
This article explores the dilemma of security investment, highlighting the need for a shift to a risk-based mindset on all levels and outcome-based performance metrics on proactive security measures to enable prioritization of initiatives and proactive resource allocation.
Risk-based mindset
Deciding how much to invest in security will often begin with a fundamental discussion of “How much should we spend?” or simply become the result of how much is left in the budget. However, how does an organization ensure this is the right or appropriate amount to invest? In security, there is always something more that could be done, one more measure that could be taken to avoid incidents or attacks.
No one can fully secure themselves from every threat, so to make a conscious decision, every organization that is not limited by regulatory constraints should instead focus on the question, “How secure can we be? What risks can we accept?” With this mindset, an organization will be equipped with a straightforward way to communicate and discuss what an initiative implies for the risk level accepted and, additionally, what cost is associated with reaching a certain level of protection.
Outcome-based performance metrics on proactive security measures
While a risk-based mindset is important and a prerequisite, it is not enough to make informed decisions. Organizations need hard metrics that can be assessed and compared, and the size of an investment is not an indicator of IT protection. The challenge lies in the fact that not all investments of the same size result in the same levels of protection. This discrepancy stems from factors such as the effectiveness of the chosen security solutions, the organization’s unique threat landscape, and its overall security level.
To bridge this gap, organizations should use outcome-based performance metrics for evaluating security investments and measures. Instead of using the size of investments as an indicator of security, organizations should use metrics that focus on measurable protection level outcomes. These metrics provide a better overview of the actual impact of security initiatives and investments. By analyzing how these metrics change with each proposed investment or configuration, organizations can objectively discuss and determine acceptable levels of security and balance that with the associated cost.
Examples of performance metrics
Time to resolve
Definition: Time to resolve is the average duration it takes to resolve a cybersecurity incident or breach from when it is detected or reported.
Purpose: This metric evaluates the organization’s ability to not only respond quickly but also to effectively contain and eliminate the threat. A shorter time to resolve implies a more effective incident handling process.
Average patching frequency
Definition: How often an organization applies security patches and updates to its systems and software on average in terms of a time interval, such as days or weeks.
Purpose: The metric reflects the organization’s commitment to keeping its software and systems up-to-date with the latest security patches. A higher patching frequency indicates a proactive approach to addressing known vulnerabilities and reducing the attack surface.
Approach
For an organization to assess the result of an outcome-based metric and use this in a decision, it is necessary to adapt and analyze this in relation to the specific organization. To construct and adapt a metric, an organization can follow these steps:
1. Baseline Assessment
Clearly define metrics important to the organization and conduct a baseline assessment based on historical data. By gathering this data, it will serve as a benchmark against which the potential impact of the investment can be measured.
2. Estimating the Change
Construct an estimate of the potential positive effect that could be achieved if the investment, initiative, or configuration change were to be made. This could, for instance, include the use of suppliers’ customers as benchmarks to assess what benefit could be achieved.
3. Evaluation and Informed Decision-Making
Evaluate the Return on Investment (ROI) of the proposed security investment by comparing the projected ROI in terms of actual protection levels achieved against the organization’s risk appetite expressed in hard metrics and the investment cost.
It is important to note that one investment in a security measure may have a potential positive impact on more than one security metric.
Example: Illustrating the Concept with Time to Respond (TTR)
A powerful example of an outcome-based security performance metric is the “Time to Respond” (TTR). TTR measures the speed at which an organization can detect and mitigate a cyber threat once it is identified. Organizations with shorter TTRs are better equipped to minimize the potential damage of a breach. By utilizing TTR as a metric, organizations can quantify the effectiveness of their incident response strategies and identify areas for improvement.
This concrete data allows for informed decision-making that goes beyond abstract risk assessments. The metric data can also be leveraged when considering an investment that could potentially reduce the TTR significantly but would imply a substantial cost. Comparing these aspects can give organizations a powerful tool to make informed and fact-based decisions.
Optimizing Budget for Maximum Protection
Consider a scenario where two different organizations allocate the same budget to cybersecurity. While this might seem like an equal investment, the actual protection level could significantly differ based on the configuration of security resources and initiatives. Outcome-based metrics as discussed provide a framework for organizations to optimize the security budget according to their risk appetite and support the prioritization of resources that is inevitable. By identifying the most effective security measures for their unique threat landscape, organizations can maximize their protection levels within the same budget constraints.
Conclusion
All organizations and cybersecurity responsible roles should establish a risk-based mindset when assessing investments and to be secure enough requires a focus on the outcome. With a risk-based mindset in the process of deciding how much investment to make in cybersecurity and information security, the organization is well-equipped to achieve constructive discussion with a common basis. To this, by implementing the usage of outcome-based metrics the decision will be further assisted with facts that are comparable both internally and externally.
With this management and cybersecurity responsible can make sound decisions on how much to invest, while at the same time equipping them with an opportunity to understand what a decision of not investing entails for the level of threat. Conclusively this would ensure organizations that the investments have an advantageous impact on the company’s level of protection.
Where are you in your path regarding strategies for information security and cybersecurity? We offer support in your specific journey, and we invite you to discuss this further with us.
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With the rising cost pressures, automation has become an organisation’s new way of operating and innovating. Today we see many ERPs adding advanced technologies to their products along with the automation of more and more business processes. New technologies like ML and RPA play a key role in how enterprise business process modules are written. These advancements come as no surprise given that ERPs have always been driven by the goal of increasing the efficiency of business processes and saving time spent on performing manual tasks.
At its core, intelligent process automation is the use of emerging technologies that can enable business process improvements and redesign. Such automation products can be presented in numerous ways according to the technology or the use case they deliver.
Industry Trends
Advances in ML are providing organisations with an increasing number of automation options. On one hand, ERPs are acquiring or partnering with automation experts to accelerate their RPA and Machine Learning portfolio while on the other end, niche and specialised automation vendors are focusing on developing connectors with core enterprise software. For instance, SAP has acquired Contextor – a European leader in design & RPA, and Signavio – a process automation startup to build its process intelligence offering. Oracle has partnered with Automation Anywhere and UiPath to develop its RPA capabilities.
Niche products for finance management provide advanced and specialised automation solutions for finance processes such as automated financial close management that include unified & automated platforms for accounts receivables and intercompany financial management. These solutions help companies to modernize & use best-in-class practices for their financial processes. Such products support different ERPs and therefore can help to automate functional areas working across multiple ERP systems.
Balancing Cost vs. Complexity
Niche solutions provide a greater depth of functionalities and may involve less cost and complexity than an ERP. We have seen companies preferring a purpose-built e-solution rather than wanting to expand the capabilities of ERP. However, if the depth of functionalities is almost the same as that of ERP capabilities, then it may involve less hassle to expand the capabilities of existing systems like ERP.
Organisations, thus, today face the challenge of choosing from a wide range of options, be it leveraging the automation capabilities of an enterprise suite or using a specifically designed solution for a given business function. With this fast-growing market and increasing cost pressures, the burden falls on companies to carefully evaluate not only their present needs but also anticipate the future scope to make the right decision in choosing an automation solution. Otherwise, they run the risk of building multiple fragmented and siloed solutions across their IT landscape.
Opticos supports clients with formulating automation strategies and implementing solutions using ERP or niche products, as per your organisation’s specific requirements.
Authors: Abhishek Kale, Jasmeen Kaur and Johan Saks
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Even as sustainability takes centre stage across the value chain in a conscious effort to minimise the impact on the environment, governments are leveraging regulatory frameworks as powerful catalysts for fostering eco-conscious change. At this pivotal juncture, corporate leaders are faced with an essential decision; to acknowledge sustainability as a corporate duty and a strategic necessity.
Nils Andersson, Sustainability Consultant at Opticos, sat down with Göran Kördel to discuss various aspects around sustainability, opportunities, challenges, and get an insght into Boliden’s journey in this important area.
Contents
- About Boliden
- Guest Spotlight: Göran Kördel
- Focus on Digitisation
- The Approach to Sustainability
- The Double Role of IT in Sustainability
- Data-Driven Approach to Sustainability Reporting
- The Quest for Data and EU Sustainability Regulations
- The Evolving Role of the CIO
- Top 3 Priorities for CIOs in Sustainability
About Boliden
Boliden is a leader in the sustainable extraction and processing of base and precious metals. Through technical innovation and expertise in mining and smelting, Boliden delivers high-quality products such as zinc and lead ingots, copper cathodes, gold, and silver granules. Their operations span across the Nordics and include prospecting, mining, smelting, and delivery to industrial customers in Europe. Read more about Boliden.
Guest Spotlight: Göran Kördel
Orchestrated under the capable leadership of Göran Kördel, the Chief Information Officer (CIO) of Boliden, the company has a unified IT organisation, where the CIO is responsible for aligning IT with the business goals. With a career spanning over two decades, Göran´s journey through the IT industry is marked by transformative roles and influential leadership, making him a driving force in adapting technology for modern challenges. Göran Kördel´s journey into the IT world began at Ericsson and then continued to Sandvik, where he held positions as President, CIO and Vice President. Göran has paved his way through the industry, and in his current role as CIO at Boliden, he continues to be a leading force in adapting technology and IT for the mining industry and beyond.
Focus on Digitisation
The strategic adoption of digitalization is a fundamental driver for achieving sustainability goals within any organisation. Recognising the significance of digitisation in the pursuit of sustainability, Boliden has focused on transforming its operations to become more sustainable, where the IT function plays a crucial role in the company’s success.
The company’s primary focus is on production, resulting in an emphasis on Operational Technology (OT). While we discussed the digitisation of Boliden’s operations, Göran emphasised that there are three important aspects to digitising the company operations:
- Supporting production with automation: This involves connecting machines and sensors to optimise production.
- Developing data analysis: The company collects comprehensive data from connected machines, enabling advanced analysis.
- Digitising employee ecosystem: Today´s digitisation includes all employees, not just executives and IT users as it was in the past.
The Approach to Sustainability
Sustainability within an organisation can’t be the sole responsibility of a single department; it requires a collaborative effort. When it comes to inter-departmental collaboration to support the company´s sustainability goals, Göran identifies two cornerstones that shape his work:
Focus on sustainable production: Boliden aims not only for electrification but also for sustainable metal extraction. Despite the company already establishing itself as a leading player in sustainable mining globally, they are striving to challenge themselves by raising the bar. “We are currently producing metals with a significantly lower CO2 footprint than the industry in average, but we must continue to evolve and improve,” Göran emphasized, with goals such as a 40% reduction in absolute CO2 emissions in Scope 1 & 2 by 2030 compared to 2021 as the base year and carbon neutrality by 2050 as guiding principles for their corporate strategy.
We are a big contributor to the circular economy by recycling electronic scrap, car batteries, and steel mill dust. While we explored the role of technology in advancing the company’s sustainability objectives, Göran highlighted two significant challenges Boliden encountered on its sustainability journey.
Firstly, the deployment of electric vehicles for transportation, while technologically feasible, presents a formidable task in replacing diesel-based vehicles.
Secondly, the transformation of core processes, such as smelting and blasting, particularly in endeavors like green steel production, necessitates a protracted process development timeline, illustrating the complex nature of process transformation in achieving sustainability goals. These challenges underscore the nuanced interplay between technology and operational change essential for sustainability success in the mining industry.
Source: www.boliden.com
The Double Role of IT in Sustainability
IT can play an important role for organizations in their sustainability operations. Göran identifies two cornerstones that shape his work:
- Technology´s contribution to environmental efforts: Göran emphasises the crucial role that IT can play in the two primary areas of carbon dioxide reduction. By electrifying transportation and optimising production processes to reduce CO2 emissions, the IT team creates opportunities to use technological innovations like artificial intelligence (AI) to drive improvements.
- Sustainable IT delivery: The second area is the importance of sustainability within the IT department. Through actions like hardware reclamation and extending the lifespan of devices, such as laptops and servers, IT can contribute to more sustainable technology production. “But we can do much more” Göran explained, mentioning opportunities like prolonging the lifetime of the hardware, setting data centers cloud services, and optimising energy consumption by shutting down systems during idle times.
Source: www.boliden.com
Data-Driven Approach to Sustainability Reporting
With the implementation of a data-driven sustainability program, sustainability reporting has become an increasingly important part of business operations. “We´ve reported on sustainability for many years and have various environmental permits that need to be reported to authorities. Also, we have investors demanding more and more sustainability reporting,” Göran shared. The increasing emphasis on sustainability takes on a new form.
The European Union’s Corporate Sustainability Reporting Directive (CSRD) is a directive for sustainability reporting, and the requirements for quality and follow-up are becoming increasingly equivalent to those for financial reporting. “Sustainability reporting isn´t new, but the new legislation increases the requirements on what should be reported as well as traceability and frequency. Previously, sustainability reporting could have been done using standard tools like Excel and was somewhat less structured. Now it has to be done in a more controlled way, which requires systems,” he explained.
In line with increased transparency and accessibility, data reliability has become more important. “We´ve been working on setting up a data platform in a mesh structure where we can conduct data governance. It´s about defining who owns the data, quality-assuring the data, and so on,” he explained. He further describes their efforts to automate more of the process to reduce manual effort. “We´re trying to automate wherever possible, so there’s less manual intervention. Of course, manual uploads are still needed sometimes, but we’re trying to automatically gather data from primary sources or sensors.” These efforts encompass not only general data management but also now emphasise sustainability data, reflecting the growing importance of data management for the company.
The Quest for Data and EU Sustainability Regulations
While discussing the amount of data to be collected in sustainability reporting and its complex nature, Göran said,“The actual challenge lies in collecting data and knowing where to fetch and harmonise the data. The challenge isn´t the output, but rather the collection of data. When talking about CSRD, it covers the entire spectrum of data. For example, the EU demands hundreds of KPIs across the entire ESG (Environmental, Social, Governance) spectrum. This means a double materiality analysis must be carried out to identify what´s important – both financial and other influencing factors. Therefore, it involves a significant amount of environmental data, like CO2 emissions, and different types of water and air quality, which are important for us.”
When asked about Boliden’s preparedness for the EU´s new sustainability legislations, such as CSRD, and upcoming legislation like Eco-design for Sustainable Products Regulation (ESPR), Göran said, “We have been preparing for the EU´s sustainability reporting, CSRD, for a year as we recognised that it would take a long time. Further, we’ve been using basic reporting tools until now; moving forward, a comprehensive solution would be required in line with the growing complexity.”
The Evolving Role of the CIO
When asked about how Göran´s role as CIO has changed with the increased importance of sustainability aspects, he said, “The significance of IT has grown and become more prominent over time, and sustainability is the latest and important metric in IT”. This trend is visible across many companies, and Boliden is no exception. However, with the increased presence of IT within the business, collaboration between IT and other departments needs to be closer and more integrated than ever before. While sustainability holds a significant place in the company´s strategy, according to Göran, it hasn´t necessarily fundamentally changed the CIO’s role. He sees it as an opportunity for IT to step forward and make meaningful contributions.
Future Trends
Speaking about the focus of CIOs moving forward Göran said, “It´s hard not to mention AI and advanced analytics, as these technologies enable more selective and enhanced process management. They assist in identifying, understanding, and optimising changes that can lead to a better environment. As for other trends, I believe an extremely critical success factor is a close collaboration between IT and the business. This isn´t unique to sustainability itself, but I consider it of tremendous importance”.
Top 3 Priorities for CIOs in Sustainability
Finally, Göran believes that the three most important aspects a CIO needs to consider while addressing sustainability goals are:
- Listen to business executives to be able to support and understand their pain points regarding sustainability.
- Proactively work on pilots, development, and improvements using analytics to conduct analyzes and enhancements.
- Evaluate how IT can be leveraged to address Sustainability goals and integrate such discussions into the IT roadmap
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Even as businesses continuously innovate and scale new growth trajectories, adopting best practices in your sourcing lifecycle can be a key enabler to delivering business objectives. Supplier optimisation remains a key focus area in the Sourcing Toolkit of a CPO and finding the right balance in your supplier management strategy can make a significant difference to your bottom-line while delivering a sustainable competitive advantage. This article offers a perspective on the importance of supplier optimisation in your Sourcing lifecycle.
Introduction
In today’s dynamic & rapidly evolving business landscape, strategic sourcing has become a crucial function and is an integral part of the CxO discussion board. In a nutshell, Strategic sourcing is a procurement strategy that focuses on obtaining products (goods/services) in a way that aligns with the organisation’s overall business objectives. It involves a systematic and holistic approach to identify, evaluate, and select suppliers to optimise value, reduce costs, and mitigate risks.
The Procurement Lifecycle may be best visualised as illustrated in Exhibit 1. The upstream areas usually fall under the realm of ‘Strategic Sourcing’ while the tactical downstream functions are classified as ‘Operational Procurement.’
Exhibit 1: The Procurement Lifecycle
As part of the procurement lifecycle, supplier optimisation plays an important role irrespective of the maturity of your sourcing function in achieving operational efficiency, cost reduction, and overall business success. So, how can one ensure the most optimal number of suppliers for a particular good or service while balancing risk and quality? For example, a long tail of suppliers may lead to operational inefficiencies and value leakage while too few may enhance your business risk significantly. How do you arrive at an optimal solution?
We offer a few perspectives towards achieving this objective.
1. Develop a Robust Supplier Evaluation Framework
One of the initial steps in supplier optimisation is to establish a comprehensive supplier evaluation framework. This framework should include key performance indicators (KPIs) aligned with business objectives, such as quality, delivery, cost, innovation, and sustainability. By objectively assessing suppliers based on these criteria, organisations can make informed decisions and identify the most suitable partners for their strategic sourcing initiatives.
2. Leverage Sourcing tools and best-practice frameworks in your Sourcing Process
While several tools may be implemented at various stages of the sourcing lifecycle, we highlight a few well-known tools that are extensively used in the industry.
2.1. The Kraljic Matrix:
Perhaps the most widely used tool by procurement and supply chain professionals for supplier portfolio evaluation, the Kraljic Matrix is a function of two parameters: supply risk and profit impact. A supplier is classified under one of the four quadrants of the Kraljic Matrix based on the function of these two parameters. For example, a supplier is classified as strategic if the sourced product/service is “business critical” while impacting the bottom-line of the company the most. Using the tool in classifying suppliers’ products and services can address supply risks while supporting strategy development.
The Kraljic Matrix is an integral part of the Opticos consultative toolkit. For example, stratification of suppliers into strategic and non-strategic at a global Swedish conglomerate client of Opticos, enabled a differentiated approach to the procurement optimisation challenge, and ultimately led to a total initial cost saving of ~120 MUSD, and a projected annual saving of ~15 MUSD.
Exhibit 2: Kraljic Matrix for Supplier Portfolio Evaluation
2.2. Total Cost of Ownership (TCO)
TCO analysis is a comprehensive approach that goes beyond the initial purchase price of a product or service and considers the entire lifecycle costs. It involves evaluating various cost components such as acquisition costs, operational costs, maintenance costs, and disposal costs.
By conducting TCO analysis, organisations can make informed decisions based on the total cost impact rather than focusing solely on the purchase price. This helps identify opportunities for cost reduction and value enhancement throughout the sourcing process.
3. Foster Strong Supplier Relationships
Building strong and collaborative relationships with suppliers is fundamental to supplier optimization. By establishing open lines of communication, organisations can enhance transparency, trust, and mutual understanding. Regularly engaging with suppliers, conducting face-to-face meetings, and involving them in the product development process (especially the strategic category) can foster innovation and drive continuous improvement. Additionally, organisations should consider conducting periodic supplier performance reviews to address any concerns and reinforce the importance of meeting expectations.
4. Embrace Technology and Data Analytics
Leveraging technology such as e-sourcing platforms, e-procurement systems, and supplier relationship management tools can improve process efficiency as well as enable your organisation to gain trust with your current and prospective suppliers by bringing transparency in your sourcing and procurement processes. Further, Advanced analytics can help identify patterns, trends, and potential risks, enabling organisations to make data-driven decisions, negotiate better contracts, and optimise supplier portfolios.
5. Practice Supplier Diversity and Risk Mitigation
Supplier optimisation should extend beyond cost reduction and performance improvement. Organisations should actively promote supplier diversity by considering businesses owned by underrepresented groups, fostering a more inclusive and sustainable supply chain. Diversifying the supplier base can enhance innovation, support local economies, and contribute to a positive brand image.
Furthermore, effective risk management strategies are essential for supplier optimisation. Organisations should identify and assess potential risks associated with suppliers, such as geopolitical instability, natural disasters, or financial vulnerabilities. Developing contingency plans and alternative sourcing options can help mitigate potential disruptions and ensure business continuity.
6. Encourage Continuous Improvement and Innovation
Strategic sourcing is not a one-time exercise but a continuous process of improvement and innovation. Organisations with a mature Sourcing and Procurement functions encourage suppliers to embrace continuous improvement methodologies, such as Lean Six Sigma to eliminate waste, reduce costs, and enhance quality. Further, engaging suppliers in collaborative innovation initiatives, seeking their expertise in product development, process optimisation, and sustainability practices are important levers in achieving competitive advantage. By fostering a culture of continuous improvement, organisations can stay ahead of the competition and drive long-term supplier optimisation.
The Final Word:
Even as businesses continuously innovate and scale new growth trajectories, adopting best practices in your sourcing lifecycle can be a key enabler to delivering business objectives. Supplier optimisation remains a key focus area in the Sourcing Toolkit of a CPO and finding the right balance in your supplier management strategy can make a significant difference to your bottom-line while delivering a sustainable competitive advantage.
Authors:
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As organizations look for cost effective ways of working, outsourcing non-core functions appears as an alluring prospect. But before you hand over your operations to third parties, it is worth pausing to consider the risks associated with your sourcing approach. Starting with an overall capability perspective entails several benefits over service first approach, and it enables you to build a strategic approach to sourcing.
Outsourcing is an effective way for companies to focus on their core competencies, reduce costs, and access specialised expertise. However, the success of outsourcing initiatives is not guaranteed, and it is essential to take a strategic approach where one of the most important elements is to start with an overall capability perspective rather than a service focus.
When starting with a service focus, companies tend to focus solely on the services that will be provided by the service supplier. Such an approach does not take into account the company’s broader capability portfolio, which could lead to gaps in capabilities, ineffective management of supplier relationships, and suboptimal outcomes.
Figure 1. Potential value leakages in the sourcing process
In contrast, starting with an overall capability perspective allows companies to take a more holistic approach to sourcing. This perspective involves identifying and assessing the key capabilities necessary to ensure an optimally functioning and strategically aligned service delivery.
An overall capability perspective also allows for companies to develop a more strategic sourcing plan. The initial capability assessment should serve as the foundation for the transformation roadmap. Any capability gaps identified should be visualized, for example in a heat map, prioritised and addressed as part of the overall service delivery transformation plan – outlining the steps required to enhance or build the necessary capabilities, such as governance, processes, and technology, to close the gaps. This transformation plan will thus to a greater deal focus on achieving the company’s strategic objectives, rather than just accomplishing specific service targets.
Figure 2. An example of the heatmap illustrating capabilities and their maturity levels
The capability assessment can also be a useful tool in the service provider selection, where selection criteria should include ability to proactively support in providing and building the key capabilities. The transformation plan will then enable a joint focus and common strategic priorities.
In essence, starting with an overall capability perspective enables organizations to take a more strategic approach to sourcing and how to outsource. It involves considering the long-term implications of the sourcing approach, including the impact on the organization’s capabilities and the ability to meet future business needs. This approach also allows organizations to identify the right service providers who can help build capabilities while delivering the required services.
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This is how you can take your first step to an actionable Data Strategy
To stay competitive, companies harness data to enhance customer experience, streamline operations, and carve out a sustainable advantage. Leveraging AI and advanced analytics, they tackle challenges from predictive maintenance and pricing models to organizational optimization and digitizing products.
Success with advanced analytics hinges on data accuracy and sustainable data sourcing. At Opticos, we have found that a pragmatic, focused data strategy is crucial for companies aiming to become data- and analytics empowered. This strategy facilitates the extraction of value from data, paving the road to success.
Many businesses grapple with fragmented IT landscapes, point solutions, lack of data ownership, and poor integration. As a result, analytics teams are burdened with data collection and cleaning rather than focusing on valuable analysis and insights.
Concerns about data quality frequently surface. Businesses periodically launch data quality and master data initiatives. But without robust data governance, data quality tends to decline over time. Hence, achieving accurate data often depends more on luck than a solid business practice. The remedy? An actionable data strategy.
To align the organization on data-related objectives and to overcome the challenges above, Opticos provides three recommendations:
- Use Case-Driven Approach: Identify, evaluate, and prioritize use cases that tie business needs to value, targeting relevant data assets and datasets. For instance, forecasting customer order volumes in supply chain management could use historical and weather data.
- Prioritized Data Asset Governance: Instead of tackling organization-wide data ownership head-on, establish ownership of data assets for prioritized use cases. Ideally, process or function owners will own the data from source to consumption, regardless of the storage and processing systems. Start with use cases, like customer order forecasting, where assets include product inventory, article details, orders, and sales forecasts. Assign ownership from source to consumption, independent of the data’s system journey.
- Transparent Data Architecture: Establish a clear blueprint detailing capabilities to capture, ingest, store, process, share, and consume data for prioritized use cases. Setting up systems for data discovery, monitoring, and governance is also crucial. Emphasize transparency and communication so all stakeholders understand their roles in delivering high-quality data. For instance, use diagrams to map out data flow for each prioritized data asset: from source systems like CRM, through data storage like Data Lake, to Business Intelligence reporting tools.
Furthermore, we recommend a phased data strategy implementation, detailing the first phase and keeping subsequent phases indicative. As you begin implementing, the roadmap’s details become more distinct and defined.
Illustration 1 – Illustrative template for a phased, use-case-driven Data Strategy execution roadmap
An actionable data strategy implements data management practices and governance structures that enable efficient data sharing and continuous quality improvement. Once initial success is evident, the process can be scaled and replicated across other use cases.
Guiding your Data Management Journey
At Opticos, we enable organizations to leverage business benefits by building pragmatic, and holistic data management practices. Drawing from our extensive client experience and methodology, we’re here to guide your data management journey from strategy to implementation.
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Finding the Sweet Spot in your business: Mastering the Balance between Standardization and Flexibility
In the dynamic landscape of modern business, organizations struggle to balance standardization and flexibility. The extremes of both these concepts are often clear-cut, but the real challenge lies in navigating the middle ground. This short article explores the balancing act, offering insights to help businesses calibrate their approach to standardization and flexibility.
Decoding Standardization and Flexibility
Standardization, in essence, is the establishment of a set of rules or procedures that dictate the execution of a specific task or process. It extends to products and services as well, aiming to deliver a consistent experience to the customer or the organization providing it. The advantages of standardization are numerous – it enhances efficiency, consistency, and predictability, reduces the likelihood of errors, streamlines processes, and ensures quality performance, thereby saving time and money.
Flexibility, on the contrary, is the capacity and infrastructure that allows an organization to adapt and modify processes, products, and services in response to evolving customer needs or market conditions. This adaptability fuels innovation, agility, and customization, enabling companies to respond swiftly to market shifts or customer requirements, which can help them stay ahead of the competition.
Assessing Your Business Needs
The first step in finding the right balance between standardization and flexibility is to assess your business needs. This involves considering the industry you operate in, the nature of your business, and your customers’ needs. Certain industries, such as manufacturing, might benefit more from a standardized approach, while others, like technology, might require greater flexibility to keep pace with innovation and changing customer needs. This assessment should be conducted from both top-down and bottom-up perspectives, containing strategy to implementation across all levels.
Illustration 1 – Dimensions and Perspectives across the Organization impacted by choices related to standardization and flexibility.
Assessing Your Processes, Products, and Services
A thorough evaluation of your processes, products, and services is crucial to determine where standardization and flexibility are most appropriate. Identify tasks or processes demanding high consistency and efficiency where standardization can benefit. Conversely, pinpoint areas that require greater flexibility to adapt to changing customer needs or market conditions.
The Pros and Cons of Standardization and Flexibility
It’s essential to weigh the advantages and disadvantages of standardization and flexibility for your business. While standardization can enhance efficiency, consistency, and predictability, flexibility can foster innovation, adaptability, and customization. However, too much standardization can suppress creativity and innovation, and too much flexibility can result in a lack of consistency and predictability.
Mastering the right balance
Mastering the right balance between standardization and flexibility requires carefully evaluating your business needs, processes, products, and services. Identifying areas where standardization can offer benefits and flexibility is needed to adapt to changing customer needs or market conditions – is crucial. A flexible approach can help you stay ahead of the competition, while standardization can provide consistency and efficiency. Additionally, a holistic view is required to address several aspects together as there may be a slight conflict between them. Some considerations may guide this decision in choosing the appropriate path forward.
Illustration 2 – Considerations when assessing processes, products, or services.
Implications for the IT Operating Model
As mentioned, disruptive industry forces present new opportunities, threats, and organizational requirements. The rapidly evolving competitive landscape introduces new challenges for CIOs. A traditional approach to IT delivery is no longer viable. The IT Operating Model should be designed to dynamically match the different features of the Digital, Evolving, and Legacy Business. Companies can adopt a multi-speed approach to IT delivery to support a dynamic business model and evolve at an increasing pace while trying to contain costs. Multi-speed IT enables business needs to be delivered at differing velocities, thereby striking the right balance between standardization and flexibility.
In Conclusion
Balancing standardization and flexibility is crucial for success in today’s business environment. Companies must evaluate their business needs, processes, products, and services to determine where standardization and flexibility are most appropriate. By mastering the right balance, businesses can achieve greater efficiency, consistency, and predictability while fostering innovation, adaptability, and customization.
We invite you to engage in further discussion on this topic. We are more than willing to share our insights to help your business improve.
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How do you choose the right implementation partner(s) for your ERP program?
ERP programs are often considered one of the largest investments for organizations and are associated with operational and financial risk, and are also a driver for change from many perspectives.
That is why it is essential to form a solid strategy for sourcing an ERP implementation partner early on. Considering, for instance, make versus buy strategy, pricing model, sourcing objects, supplier capacity, and capabilities to engage the right partner(s) in a timely manner and to help deliver on the transformation objectives.
Forming an ERP Implementation Partner Sourcing Strategy that fits your organization
Forming the ERP Implementation partner sourcing strategy will likely be a collaborative exercise where companies often find themselves considering the same questions more than once. We at Opticos recommend formulating and agreeing on a few Strategic Drivers to form a solid foundation – as a starting point. These drivers or business values will then provide guidance in the detailing of the strategy and act as a basis for making the right decisions for your organization.
These areas are generally part of an ERP Implementation Partner Sourcing Strategy:
- Strategic drivers or business value
- Sourcing direction (sourcing objects, supplier selection, make or buy)
- Governance
- Commercial engagement model
When detailing a sourcing strategy, you are advised to consider a few critical and strategic areas and questions:
Illustration 1 – ERP sourcing strategy – key areas to consider
The answers to these questions, and hence the sourcing strategy, will vary depending on your organization’s existing capabilities, value drivers, and relationships with existing and preferred vendors.
The Sourcing Process
When the first version of the strategy is set, it is time for the actual selection of partner(s). We recommend qualifying the supplier’s capabilities through a collaborative sourcing process (as opposed to a traditional RFP) to develop requirements, ways of working, and validation of the cultural fit for the organization. The process will also help form a better understanding of what capabilities need to be developed in-house or purchased from external suppliers.
While the strategy will not solve all problems, it will keep organizations on the right track when making important decisions. Please remember that the strategy should be seen as a living document and might have to evolve over time!
To summarize, at Opticos, we strongly believe in considering the following recommendations to boost your journey toward finding the right partners:
- Set the sourcing strategy early and then let it evolve over time.
- Qualify the supplier’s capabilities through a collaborative sourcing process (as opposed to a traditional RFP) to develop requirements, ways of working, and validation of the cultural fit for the organization.
- Define and select strategic capabilities to retain and develop within your organization. This will support in validating what to source externally and achieve overall transformation objectives.
- Establish a solid governance structure, and engage the sponsor to allow seamless integration and clarity on roles and responsibilities across the internal organization and engaged partner(s).
It is common to have a long road to finding the right partners. Considering these recommendations might save you a bumpy ride.
Want to know more? Don’t hesitate to contact Opticos experienced sourcing professionals!
Opticos Offerings:
Sourcing and Procurement – Opticos have a strong Sourcing and Procurement capability and a proven record of supporting clients from strategy to agreement.
Digital Transformation – Our journey does not stop when the agreement is signed! Opticos also holds comprehensive knowledge and experience from supporting clients in ERP implementations and digital transformation; we provide experienced consultants supporting on the “client-side” with, for instance, project and change management.
Linnea Håkansson & Rickard Holmkvist
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ERP and PLM – competing or complementary solutions?
Is it a question of one or the other, or are the benefits of having both so great that it is an obvious choice? For most product-centric companies that are developing, producing, and selling products, it is obvious that both are needed.
Nevertheless, some trends can challenge this:
- Many companies are now applying a business model where partners supply parts of the whole product related develop-delivery process
- Many ERP suites now include PLM-like functionalities
- Products today are increasingly bundled along with services such as financing, installation, and after-sales support
Illustration 1 – ERP and PLM combined can unlock the true potential
If you go back a few years, the distinction between PLM and ERP is quite evident. PLM was used to develop, create recipes and maintain products throughout their lifecycle. ERP took the recipe developed by PLM and procured, manufactured, sold, and delivered these products, creating orders and transactions.
Even though ERP and PLM have distinct use cases, both have overlapping capabilities as we see emerging trends at the intersection of the two functionalities. ERP and PLM now include capabilities such as managing Manufacturing Bill of Materials (MBOMs), following up on development costs, handling engineering changes, and tracking products. Processes such as sourcing are shifting up in the development process and, thus, moving from the purview of ERP towards PLM. Both systems are highly critical in every large IT landscape; thus, they must complement each other.
From our experience, a product-centric organization will most likely need both systems, and the main point of discussion should be where to draw the line between them and how to integrate them to serve your organization best. We have seen that the benefits of well-integrated systems are immense for any organization, and we have listed some of them below.
Cost reduction
With an increase in data accuracy and improved ownership of data, cost reduction can be achieved in many ways:
- Improved material visibility preventing material shortages or high inventory costs
- Single source of data provides more accurate view of the operations, making it easier to find potential areas for cost savings
- Feedback from operations to R&D about product usage and quality concerns makes it possible to quickly revise and improve products in production, thus reducing future warranty expenses.
Supply Chain Resilience
A Mckinsey Report* stated that companies with end-to-end supply chain visibility are twice as likely to avoid any supply chain disruption. An integrated environment removes information gaps and provides a holistic view of the supply chain, thus building resilience.
Product Provenance
Organizations might soon face regulatory pressure to provide product and manufacturing details such as ingredients, sources, and sub-suppliers and share them with the consumer. Seamless integrations between PLM and ERP thus become a prerequisite to achieving full product traceability as it can help trace and monitor a product throughout its lifecycle – at a model level in PLM and an individual level with ERP.
Increased efficiency
ERP and PLM integration automates some processes, such as updating, transferring, and accessing product-related data. This can help employees improve productivity and focus on more critical tasks. With an integrated product data setup, the organization can easily detect errors or enhancement possibilities and thus make modifications more efficiently.
Improved collaboration
Integration enables clear communication between different departments and create alignment through single source of data. The improved collaboration between interdependent functions will reduce time to deliver new and better products to consumers, at a lower cost.
Role of ERP and PLM in IT Landscape
ERP and PLM are critical parts of a system landscape for manufacturing companies, and to maximize their benefits, it is imperative to understand their respective strengths and use cases.
Companies rely on being competitive through their products, making effective collaboration between design and manufacturing operations essential. ERP and PLM integration enables this collaboration by having complementary functionalities for design and manufacturing processes.
Essential activities for creating competitive products, such as design, development, sampling, approval, etc. are executed and signed off in the PLM system. ERP then takes the finalized products forward by managing the sourcing, operations, finance, and sales.
Illustration 2 – Comparing high-level functionality of ERP and PLM
The integration of ERP and PLM systems affects various business areas and processes, enabling synergies. To realize all the synergies, organizations must develop an interactive and effective intersection between the systems. Furthermore, the ownership of the product structure and bill of material (BOM) must be managed.
Success factors for ERP and PLM integration
Transferring data from one application to another is only one side of the coin. It is equally important to recognize that ERP and PLM integration integrates critical organizational processes, raising the need for effective change management.
Based on our experience, the successful integration of ERP and PLM depends on:
- Complete understanding of current product design and manufacturing process as well as requirements moving forward
- Assessing and identifying the current inefficiencies and developing a vision for efficient collaboration of design and manufacturing
- Complete understanding of the data involved, including how and where it is stored and how it can be used (including master data management)
- Understanding the Master Data nature of PLM and the transactional nature of ERP to make relevant decisions of functionalities and data resided in the borderline between these two applications
- It is also relevant to have this understanding while sourcing the two systems as the vendors would compete for a larger part of the IT landscape and thus try to sell components and functionalities that organizations do not need
Illustration 3 – The ERP and PLM processes running incorporated, interacting
At Opticos, we are open to engage in discussions around the ERP – PLM integration and to assist your organization in various stages of your ERP – PLM integration journey. With expertise in Digital Business Transformation, Sourcing and Procurement, Data and Change management, we can help your organization turn ideas into action.
Want to know more? Please do not hesitate to contact us.
References: * Mckinsey Report: “Taking the pulse of shifting supply chains”
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Even if the Europen Union Green Deal is about making the EU more sustainable – it could impact the day-to-day life of the CIO – in a good way. Sure, it would be obvious to start measuring and reducing greenhouse gas emissions and IT-related environmental impacts. Let’s go beyond simply CIO reporting on sustainability.
The article will include examples of how a CIO can provide value to Sustainability Strategies. Real value.
The EU Green Deal, what does it mean to the CIO?
The EU Green Deal aims to achieve climate neutrality by 2050 through reduced greenhouse gas emissions, renewable energy, and biodiversity conservation. As companies strive to meet these goals, the role of the CIO is expanding from IT management to becoming a sustainability information provider. This requires ensuring products and services comply with the upcoming Green Deal’s traceability and identification requirements. This Opticos viewpoint examines CIOs’ crucial yet unclear role in driving their companies toward sustainability. But first, let’s look at the background of the EU Green Deal.
What is the European Green deal?
The European Green Deal is a flagship project of the European Commission and a holistic approach to addressing the challenges of climate change. Some of the ambitious goals can be seen in the figure below.
Illustration 1 – EU Green Deal key figures – ( * compared to 1990)
The Green Deal covers all sectors
The Green Deal includes a variety of measures, such as promoting electric vehicles, enhancing energy efficiency in buildings, and investing in sustainable infrastructure and research and development. The Green Deal covers all sectors of the economy, including transport, energy, agriculture, buildings, and industries such as steel, cement, ICT, textiles, and chemicals. In this context, the Green Deal must deliver legislation and regulations, such as the potential use of Digital Product Passports and different Supply Chain Acts. These legislations will require how the sustainability data of products and services sold on the European market should be measured and made available to consumers, customers, partners, and suppliers.
It is important to note that the EU Green Deal differs from the UN Sustainable Development Goals (SDGs). However, the SDGs and the EU Green Deal are closely related as they promote sustainable development and address global challenges such as climate change. The SDGs provide a global framework for the EU Green Deal, and the EU Green Deal is seen as a tool to achieve the SDGs.
What does this mean to the CIO?
Traditionally, the CIO role has been viewed as a technology expert responsible for managing and implementing IT infrastructure and systems within organizations. They are now becoming key players in helping companies reach their sustainability targets. With increasing pressure on the world to reduce greenhouse gas emissions and address environmental challenges, companies are turning to their CIOs to lead in implementing sustainable technology solutions, often under the digitalization taxonomy. However, this is only part of the story. Going back a couple of years, the introduction of the GDPR law and other privacy legislation had a tremendous impact on the organizational use of privacy data. The EU Green Deal and upcoming legislation could have a similar data challenge impact on companies. This time it’s about how they communicate the sustainability data on their products and services to the public. In the not-so-distant future, a consumer of a product in the EU shall easily understand the full sustainability impact of a product or service they are about to purchase. It could be scanning a QR code in a store when buying a new TV to get the sustainability score, or it could be when buying a vacation journey online. The EU will start with complex products with a high environmental impact, but eventually, it will come to mass-produced products and services.
Using legislation to promote competition
These legislations aim to make producers compete with sustainability like they already do with price. Sites that compare sustainability scores between similar products will appear in the same way that price comparison sites already exist today. For companies that would like to compete on sustainability, it will probably be a must to be able to provide open data on sustainability scores for their products and services. WatchGuard organizations will scrutinize this data, and cheating on the data will be a business risk, with a magnitude similar to Diesel Gate’s on car emissions a few years back. Additionally, companies that today provide products and services to the public sector will face the challenge of supplying this type of information to at all being able to participate in public procurement.
Data as a carrier for environmental impact
One thing that makes the demands on data architecture even higher is that it will likely not be sufficient to provide this data on the model or article level. It could be required to provide data on an individual product level, batch, or serial number. Otherwise, it will not be possible to understand the environmental impact of transportation or evaluate the potential use of a product from a second-hand and recycling perspective. It means that new and higher demands on supply-chain-traceability and the possibility of identifying a product in a globally unique way. Many companies using legacy ERPs will realize this the hard way when discovering that meeting these demands is impossible with their current IT systems. Many companies could face costly repercussions if they delay addressing these issues. Similar to the GDPR events a decade ago, it will be more expensive the longer you wait to acknowledge this. Resources to rectify the situation will dwindle and become increasingly scarce and costly.
In the figure below, we provide examples of how CIOs can help provide value to their company’s sustainability strategies.
Illustration 2 – How can CIOs add value to sustainability strategies? Here are some ways for inspiration.
Opticos offerings
The scope of the CIO agenda is expanding, and the requirements and opportunities related to sustainability are one primary driver. There is a wide range of aspects to consider that may impact and shape the IT landscape in the future.
At Opticos, we are open to engaging in discussions around this topic and providing assistance to help clarify requirements, identify opportunities, and assist in forming the change agenda going forward for your business and specific needs.
Hans Bergström & Nils Andersson
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Environmental Sustainability is becoming an integral part of corporate strategy with changing perspectives worldwide as most organizations are making future commitments towards sustainable operations.
However, along the way, they encounter several challenges ranging from performance reporting and governance to data and technology limitations. IT and Data Strategy now sit at the heart of environmental Sustainability as they enable organizations to collect and analyze information, monitor performance, and gain actionable insights.
This article will help you navigate the critical areas and some of the pitfalls.
Why are Environmental Sustainability objectives relevant to your organization?
Decarbonization was the focus of all attention during the Climate Change Conference (COP 27) in November 2022. A factor acknowledged as a critical step in offsetting human impact on the global climate.
From a business perspective, organizations face increasing pressure from their customers, investors, governments, and regulators and are held accountable for their Environmental, Social and Governance (ESG) initiatives and actions.
Most leading organizations are now incorporating ESG and environmental Sustainability in their corporate strategy and reporting progress in their annual performance reports.
Measurements for Environmental Sustainability
Environmental Sustainability requires an organization-wide transformation program and framework for computing, assessing, and allocating greenhouse gas (GHG), climate, and environmental impacts and outcomes to the organization’s direct and indirect actions and business operations.
Illustration 1 – Opticos approach to assess and measure environmental sustainability
Therefore, organizations must establish a clear link between their operations (Scope 1, 2, or 3)*(1) with measurement parameters (CO2 equivalent, water consumption, waste, biodiversity impact) and positive or negative climate and environmental externalities.
Illustration 2 – This is how the Swedish Government announces its position and commitment
Challenges in the current ecosystem
While there has been a rapid increase and adoption of reporting standards and accountability mechanisms, many organizations are yet to align their net zero commitments to any robust process or criteria. As the Net Zero Tracker reports – More than one-third of the world’s largest publicly traded companies now have net zero targets, up from one-fifth in December 2020. However, 65% of corporate net zero targets do not yet meet minimum procedural standards of robustness.
Well, where do the organizations fall short? And why do some organizations find it challenging to set a path to achieve their environmental sustainability objectives?
Organizations face many challenges, from data shortfalls, technology limitations, and time-consuming manual processes to defining robust KPIs for reporting and obtaining ESG metrics across the value chain. A fragmented approach with a weak governance structure can even aggravate the problem further in the absence of universally accepted industry regulations and standards.
A Growing Need for Change
Organizations have realized the need to decarbonize and improve Environmental Sustainability across their value chain but often struggle to translate this ambition into action and results. Sustainability may be a relatively recent concept, but the core principles of business transformation still apply.
Leadership to accelerate a shift in the corporate strategy
Environmental Sustainability directives should trickle down from the top, i.e., the leadership and organizations need to embed environmental sustainability targets/KPIs throughout their business operations. Organizations require more than better measurement and reporting practices to achieve real progress—fundamental changes in the industry ecosystems and business models are also vital areas.
Analysis of the 26 largest publicly traded Swedish Companies shows that net-zero targets are entering the mainstream, and so are the efforts to report and govern them. However, the primary challenges include drafting and deploying a detailed plan that addresses the entire scope of the value chain.
Illustration 3 – Net Zero Tracker’s analysis of Swedish large companies
Collaboration can help you along the journey
Sustainability is a systemic concept that requires the entire value chain to collaborate. Competition, though essential, is one of many drivers for success. Organizations realize the power of collaboration as shared interests and goals incentivize them, and the growing need to invest in the health of e shared ecosystem.
It is now imperative for business leaders to take a broader ecosystem view based on an understanding of all stakeholders and go beyond engagement to enablement.
Technology as a critical enabler
Much of the critical data necessary to support environmental Sustainability resides in enterprise software systems, and if this data can be standardized, combined, and analyzed, the improvements can be substantial. Whether in individual companies or large and complex organizations, the data-driven approach is already delivering sustainability-linked dividends – from reducing waste and water consumption to calculating and subsequently lowering the carbon footprint across the entire value chain.
As the world struggles to reduce or isolate the emissions causing climate change, it’s exciting to see new digital tools and technologies coming into play to help industries meet this urgent challenge. A broader digital transformation is becoming a significant enabler for monitoring sustainability performance and driving a reduction in carbon footprint. Businesses implementing transformation programs and the right technological toolkit will find that net zero targets can be compatible with organizational growth.
How can organizations engage?
Organizations need to determine the current maturity of their environmental sustainability initiatives, understand their material environmental impact, and work towards building objectives, targets, and action plans.
Illustration 4 – Organizational Maturity Levels for Environmental Sustainability
For organizations in their initial phases of the environmental sustainability journey, existing measurement frameworks, such as GHG Protocol *(2) or IFRS Sustainability Disclosure Standards *(3), can offer a way forward to establish program guidelines and a measurement strategy and help focus on data management.
A formal, structured transformation program can be a clear solution to multiple challenges organizations face on their way to the environmental sustainability journey. Opticos has worked with clients across different industries and varied transformation objectives during the past decade.
We provide expert knowledge and help organizations develop key transformation strategies and analyze current and key success factors.
Do not hesitate to contact us to discuss this further.
Learn more:
Authors
Abhishek Kale
Johan Saks
*(1) – In short, Scope 1 direct emissions come from owned or operated assets. Scope 2 consists of indirect emissions from purchased energy, such as district heating or electricity. Scope 3 encompasses all other indirect emissions, including those that result from the company’s activities executed by e.g. suppliers and distributors.
*(2) – GHG Protocol establishes comprehensive global standardized frameworks to measure and manage greenhouse gas (GHG) emissions from private and public sector operations, value chains, and mitigation actions.
*(3) – IFRS Sustainability Disclosure Standards are intended to provide a global baseline and to be compatible with jurisdiction-specific requirements, including those intended to meet broader stakeholder information needs.
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Cost seems to be top-of-mind for most CXOs and retains a high position on the agenda.
The objective of a cost optimization programme could be to fund growth or market expansion, enable innovation in both short- and long-term perspectives, or attain or maintain market position or leadership.
Cost savings initiatives can originate from different perspectives and be quite diverse in nature. A top strategic agenda which impacts the fundamental way of doing business to address structural costs within the current operating model is one example. A selective focus on tactical and targeted improvements within certain parts of the business could be simple in its rationale but effective in optimising cost and trying out an approach.
A structured approach towards the cost savings agenda is essential.
- Ensure (swift) progress to meet determined targets.
- Choose and implement a cost-out model to meet desired scope and objective – neither too complicated nor too narrow, but “fit for purpose.”
- Facilitate necessary shift from a budget perspective to cost cutting, cost optimization or value-driven cost improvements – depending on ambition
- Ensure long-term savings and cost focus become integral to the business agenda.
- Avoid typical pitfalls and limit potential risks.
OPTICOS APPROACH TO COST OPTIMISATION
Leveraging a hypothesis-driven way of working in close cooperation and clear sign-offs from relevant stakeholders help bolster analysis and execution. Given the scope and an emphasis on cost savings, the overall approach may be tailored to meet the desired business objectives.
Opticos structured and pragmatic approach encompassing five phases to executing a typical cost-out programme.
TYPICAL SUCCESS FACTORS
There are identified factors that significantly impact cost out program success rate where effective program management helps boost progress, manage risks, and increase output.
Methods and areas to work with to help articulate, define and achieve financial goals:
- Cost optimization
- Cost transformation or Cost-out
- Cost mapping
- Cost allocation
- Cost assessments and Benchmarking
- Cost transparency
- Financial management
Areas of knowledge and expertise critical to fully establish a cost-savings agenda:
- The Sourcing and Procurement domain, e.g. address overall spending – since this often constitutes a large portion of the total cost.
- The IT Strategy and Digital Business Transformation area provide valuable insights and capabilities to address improvements within the IT and Technology space, often crucial drivers for improvements and cost savings.
- To drive real business change, broad industry experience is needed to understand the market and the industry dynamics within the industry in scope.
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Any questions about our insights? do not hesitate to reach out to:
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Choosing the right automation partner for your organization
Making a good choice among hundreds of automation partners operating across the globe can be a challenge. It’s not about finding the best partner – it’s about finding the best fit for your organization.
The path to successfully implementing automation capabilities and solutions depends on the partnership between your organization and the automation partner.
The automation partner of your choice will engage with your company long-term – as the capability area requires a long-term business commitment. Technical skills are not enough.
A compatible work culture, communication style, and the right chemistry go a long way in building a strong partnership.
Nowadays, “automation” is attracting a lot of attention because of several possible and desirable benefits. Here are some of them:
- Time savings for employees
- Reduction in errors and human mistakes
- Decrease time spent performing repetitive tasks
- Increased business capacity
However, there are also consequences and limitations when entering the area of “automation” to consider. Let us list a few of the most common:
- Cost and effort (time) to set up
- Continuous maintenance and support
- Not suited to deal with low-volume unique scenarios
Considering the above, choosing the right partner will help you to achieve your automation goals and subsequently help you to harvest the fruits of your investment.
At Opticos, we help you to evaluate future automation partners, not only from a technical capabilities standpoint but also from a cultural perspective. Our framework and methodology were developed through extensive industry experience helping customers pick the right partners.
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Minna Sivertsson of Opticos is moderating a conversation between Peter Wahlgren and Petter Rönnborg.
Theme: Global logistics and supply chain.
Peter Wahlgren has long experience in consulting and various leadership roles. Most recently, Peter has been Group CIO at Stena AB, a conglomerate primarily focused on Shipping, Properties and Retail. Peter holds several board roles and is an active advisor in the tech industry.
For most of his career, Petter Rönnborg has built and grown people’s capabilities and competencies, specifically in Strategy, Management Accounting and Corporate Finance. He currently holds a position at AB SKF as Brand Protection Manager. Before joining SKF, he was an Assistant Professor at the School of Business, Economics and Law, Gothenburg University.
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Innovation is what drives us forward. Today it is something that is invested in and commonly interwoven in business plans and formulated in business and IT strategies. Going forward, however, innovation will more likely be driven across all levels and departments rather than solely from IT and by a selected few e.g. the management, consultants or project groups. Innovation cannot be organized and governed, it is part of the culture and it must grow organically in the company’s entirety. To innovate is to re-imagine, re-defining our existence [1], it is not just another change management project.
According to Forrester “20% of CEOs will fail to act on digital transformation and put their firms at risk”. Innovation will require breaking the boundaries of any hierarchical structure. CEOs will need to be open to new ideas and letting innovators be part of defining the strategy for embracing the digital future. Creating an innovative climate will be crucial. As a result, governance models based on KPIs will become obsolete and irrelevant and ultimately a new governance landscape will emerge.
On a corporate level innovation might come to be driven by all who are interested rather than those with designated roles, allowing a freedom to be innovative. On a societal level, which we must not forget in the context of digitalization, innovation will likely be driven by and in communities of digital activists and freelancers.
Learn more about innovation in the future digital society:
Together We Innovate – Innovation in Networks rather than lone geniuses:
https://www.wsj.com/articles/SB118841662730312486
5 Innovation Keys for the Future of Work – five innovation practices:
https://www.inc.com/jacob-morgan/5-innovation-keys-for-the-future-of-work.html
[1] Götz Werner – Founder of DM (Drogerie Markt) and advocate of basic income.
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Financial management – An essential part of a healthy company
Financial management is essential for companies to survive. By planning, organizing and controlling financial undertakings you create room for growth.
A prerequisite for optimizing your costs is to understand the current situation as well as how the cost structure of where you are heading will look like. Four key points to remember when assessing costs:
- Establish the cost baseline.
- Identify and assess opportunities and risks. Analyse and break down spend.
- Develop a strategy and a roadmap. Identify where to start and your end goal.
- Track the benefits to understand if you are heading in the right direction.
To understand your cost structure and identify addressable spend it is common to look at what costs are fixed, semi-variable and variable in the short, medium and long perspective.
An example of fixed costs, only addressable in a long perspective, is a contract written in a 5-year period. A variable cost in short term is for example to stop buying consultant hours. In order to get fast results and create momentum it can be important to find which costs can be eliminated today.
By setting up a roadmap of short- and long-term cost initiatives you can visualize a timeline stating actions that are most important to start with as well as in what order cost optimizing activities should be performed. More often than not this is a timely and complex task but, quick improvements could be achieved by finding out the following:
A roadmap of activities of cost optimization
Drive the change within line organization
Permanent cost savings are best initiated and driven by the operational business with strong support by top management. It is in operations you can optimize and/or standardize your processes. Some costs are, as mentioned previously, easier to cut while other costs are the opposite – essential. Costs linked to essential processes could, instead of being cut, be optimized.
Today, there are many administrative processes that, by definition, provide low or no value to the end customer or generate no revenue, but are still essential for the company. Usually these processes have been consolidated into shared service centres which in turn could be outsourced to near- or off-shore locations. This has been a formula for cost cutting and lowering the administrative burden on employees. Instead of taking these measures it could be more cost effective to turn to technologies such as Robotic Process Automation.
Robotic process automation is the fastest growing enterprise technology today. By using RPA, companies have the possibility to automate business processes that are many times both costly and time consuming.
There are different levels of how advanced RPA can be. The less advanced levels are nowadays mature technologies with many competing vendors. Here we can find business cases to be made where case studies have shown return of investments of RPA implementation to be between 30-200% already in the first year. The business case is not only built upon increased efficiency where the processes are executed faster. By implementing RPA in existing business systems, it also helps save costs incurred due to human errors. According to estimates from IBM erroneous data input by humans costs $3 trillion per year in the US alone. By implementing RPA, errors for those certain processes are coming down towards 0%, which of course has a positive impact in a business case.
Having a cost-optimization focus is possible regardless of organization maturity, requirements for innovation and change and improving current operations. There are many different ways of achieving this; stop doing, standardizing or re-negotiating contracts. But now we also have the possibility of applying RPA, something which has emerged rapidly in the last couple of years. If you are interested in getting more information, please don’t hesitate to contact us at Opticos.
Read more about financial management and RPA by clicking on following links:
https://isg-one.com/pt/artigos/calculating-a-robot-s-tca-(total-cost-of-automation)
https://assets.kpmg/content/dam/kpmg/pdf/2016/05/rise-of-the-robots.pdf
[1] https://www.mckinsey.com/industries/financial-services/our-insights/the-value-of-robotic-process-automation
[2] https://hbr.org/2016/09/bad-data-costs-the-u-s-3-trillion-per-year
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It is easy to fall for the latest trends and buzzwords, it’s what keeps us up to date and relevant. But rarely is it completely applicable and implementable on your organisation as-is. Take the new trend of RPAs for example. Robot Process Automation is seen as a quick road to automation and most importantly cost reduction but what is often overlooked is the fact that RPAs are actions that would have been done by a human (manually) now being done by a robot (automated). Which ultimately means that an inefficient process done manually will be just as inefficient, although somewhat faster, when automated. In other words, RPAs do not improve your processes they simply make them go faster.
According to Forrester, “75% of AI projects will underwhelm because they fail to model operational considerations, causing business leaders to reset the scope of AI investments”[1]. With automation comes vast opportunities for decreased lead times and higher quality – if what is being automated is a fully functioning and effective process/activity. When investing in automating processes it is therefore important to set up a clear business case and plan for the new intelligent layer that is being added as it will require new competence for driving the improvement processes, configurations and much more.
Learn more about what RPAs are, how they can be used and what to consider when implementing them:
How to Capitalize on Robotics – Savings Drivers with Digital Labor:
How Artificial Intelligence Will Change Everything:
AI in the Workplace and the future of Robotic Process Automation:
[1] Forrester, Predictions 2018 – A year of reckoning
If you have any questions about the insights we share or are keen to turn ideas into action, please contact Mattias Gustrin, Head of Insight, +46 734 30 14 92, mattias.gustrin@opticos.se
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47 % of jobs in the United States are at risk of being automated, according to an Oxford study. OECD has found that “close to one in two jobs are likely to be significantly affected by automation” in 32 OECD countries. These statistics can be alarming at first but only if one is not prepared. Denying the inevitable will lead to a deer-in-headlights situation for all companies that have not adapted their modus operandi in time for the coming change that will affect the corporate landscape and the global society.
This is not another Orwellian prophecy – vast transformations toward an increasingly more digital society are inevitable in the next decade. Bain, amongst others, predicts that by 2030 “the global economy will likely be in the midst of a major transformation”.
Learn more about the future of employment:
AI & The Future of Work – TED Talk by Volker Hirsch
The Future of Employment: How Susceptible are Jobs to Computerisation?
OECD Social, Employment and Migration Working Papers
Labor 2030: The Collision of Demographics, Automation and Inequality
If you have any questions about the insights we share or are keen to turn ideas into action, please contact Mattias Gustrin, Head of Insight, +46 734 30 14 92, mattias.gustrin@opticos.se
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There is no denying it anymore, there is an elephant in the room and we need to address it. It is the rapid decrease in jobs during the peak of automation in the coming decade. Many studies have tried to pinpoint the vastness of the change, but we simply cannot know, all we know is we need to be prepared. Jobs as we know and define them today will change.
It is in our genes, when something seems unpleasant, we avoid talking about it. However, this topic will affect so many of us the coming year, an avoidant strategy is not an option. Either we drive the train, or we get run over by it – we must through proactivity lead the change. How well we adapt to the change is dependent on how prepared we are for it. As leaders we must consider the organizational changes that will be faced and how we can support our employees during the transition.
As individuals we will need to consider if and how we can educate ourselves in order to broaden our competence and adapt to the changing needs of the organisation where employed and by the market at large.
With the increased automation that we face, jobs that are more focused on distinctively human capabilities such as empathy and creativity will be sought after. Scary, yes, but this can also open up for many inspiring, exciting possibilities. With the inevitable need to re-define jobs that we have today, humans will be able to have the freedom to innovate, create and inspire.
Learn more about innovation in the future of work:
AI & The Future of Work – TED Talk by Volker Hirsch:
ps://youtu.be/dRw4d2Si8LA
Harvard Business School Podcast, Future of Work – Ep. 9 How firms are building strategy around AI:
https://www.hbs.edu/managing-the-future-of-work/podcast/Pages/podcast-details.aspx?episode=6820866
If you have any questions about the insights we share or are keen to turn ideas into action, please contact Mattias Gustrin, Head of Insight, +46 734 30 14 92, mattias.gustrin@opticos.se